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The Macroeconomic and Financial Management Institute of Eastern &Southern Africa (MEFMI)
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THE EFFECTIVENESS OF OPEN MARKET OPERATIONS IN
MONETARY POLICY IMPLEMENTATION: THE CASE OF KENYA
by
GODFREY KAMPAN PUTUNOI
MEFMI Candidate Fellow
Monetary Policy Implementation
(Open Market Operations)
CENTRAL BANK OF KENYA
Mentor: Prof. Sylvanus Ikhide
A technical paper submitted in partial fulfillment of the award of MEFMI fellowship
2015 1 Contents
LIST OF FIGURES …………………………………………………………….……………………………………………………...………..3 LIST OF TABLES……………………………………………………………………………………………………………….…...…………..3 LIST OF ABREVAITIONS………………………………………………….……………………………………………………………….…4 DEFINITIONS………………………………………………………………….………..……………………………………………………….5 Abstract ...................................................................................................................................................... 5 1. INTRODUCTION .................................................................................................................................. 7 1.1. PROBLEM STATEMENT ................................................................................................................ 19 1.2. JUSTIFICATION ............................................................................................................................. 20 1.3. OBJECTIVE OF THE STUDY ............................................................................................................ 21 1.4. RESEARCH HYPOTHESIS ............................................................................................................... 22 1.5. LITERATURE REVIEW .................................................................................................................... 22 2. FINANCIAL MARKETS DEVELOPMENT AND MONETARY POLICY IMPLEMENTATION ............... 2625 3. MONETARY POLICY FRAMEWORK AND PROCEDURES......................................... 3736 4.0 DATA ANALYSIS AND PRESENTATION ........................................................................................... 4746 4.0 Introduction ............................................................................................................................. 4746 4.10 Model set up .......................................................................................................................... 4746 4.1.2 Test for co-integration ........................................................................................................... 4948 5 RESULTS, RECOMMENDATIONS AND CONCLUSIONS ................................................................. 5654 2 LIST OF FIGURES
Chart I:
Short term interest rates in Kenya …………………………………………………………...15
Chart II: OMO and the Interbank Money Market……………………………………………..16
Chart III: OMO and Interbank Rate for Kenya 2014……...……………………………………42
Chart IV: Banks Voluntary and Excess Reserves ……………………………………………..43
LIST OF TABLES
Table1. Test for stationarity results…………………………………………………………48
Table II: co-integration test…………………………………………………………………..49
Table III: VAR Lag Order Selection Criteria…………………………………………………50
Table IV: Reduced VAR Model Estimates ………………………………………………..50
3 LIST OF ABBREVIATIONS
CBI - Central Bank Independence
CBK – Central Bank of Kenya
CBR – Central Bank of Kenya Rate
GOK – Government of Kenya
MODM – Monetary Operations and Debt Management
MPC – Monetary Policy Committee
OMO – Open Market Operations
IMF – International Monetary Fund
SSA- Sub-Saharan Africa
KIPPRA- Kenya Institute for Public Policy and Research Analysis
4 DEFINITION OF TERMS
Monetary Policy: In general, monetary policy is defined as the set of procedures and measures
taken by the monetary authorities to manage money supply, interest and exchange rates and to
influence credit conditions to achieve certain economic objectives.
Financial market is a market that brings buyers and sellers together to trade in financial assets
such as stocks, bonds, commodities, derivatives and currencies. The purpose of a financial
market is to set prices for global trade, raise capital and transfer liquidity and risk. Although
there are many components to a financial market, two of the most commonly used are money
markets and capital markets.
Regression Analysis: Regression Analysis is concerned with the study of the dependence of
one variable, the dependent variable, on one or more variables, the explanatory variables, with
a view to estimating and / or predicting the population.
The test of normality: normality tests are used to determine whether a data set is normally
distribution or not.
Stationary series: this is a time series data where the mean, variance and covariance remain
constant overtime.
Co-integration: is the statistical implication of long run relationships between variables.
Purely random walk/white noise: We call a process purely random walk or white noise if it
has a zero mean, constant variance, and is serially uncorrelated.
5 Abstract
This paper investigates the effectiveness of open market operations in monetary policy
implementation in Kenya. The issue is tested empirically by assessing the impact of a monetary
policy shock on output, prices and the nominal effective exchange rate for Kenya using
quarterly time series data spanning1997Q4–2014Q1. Relying on techniques commonly used in
the vector autoregression (VAR) literature, the main results suggest that an exogenous rise in
the Repo rate tends to be followed by a decline in prices and an appreciation in the nominal
exchange rate but has insignificant impact on output. The study recommends that for monetary
policy to be more effective in Kenya, further market deepening and growth of the financial
sector to support monetary policy implementation is necessary.
Key words: Monetary policy, Monetary Policy Implementation, Open Market Operations
6 1.
INTRODUCTION
a)
Background Information
The main goal of monetary policy for most central banks is to maintain the internal and
external value of the domestic currency. In the domestic economy this means to keep inflation
low and stable. However, in a liberalized economy, central banks cannot control inflation
directly, rather, they attempt to do it indirectly by affecting interest rates or the quantity of
money and credit in the economy. Maintaining price stability is crucial for a proper functioning
of a market-based economy. It encourages long-term investments and stability.
Monetary policy has undergone significant changes over the years. Exchange rate pegs1 or
bands, monetary aggregate targets2 and inflation targets3 have at different times gained favor as
the mainstream intermediate objective that guides policymakers in their pursuit of the ultimate
objectives Malcolm (2006). A number of countries have currently adopted inflation targeting
more than a decade ago and their aim is to put in place a credible framework that avoided the
drawbacks of previous policy regimes. In New Zealand, Canada and Australia, for example,
inflation targets replaced ad hoc regimes that were considered intellectually unsatisfactory and
1
Lesotho, Swaziland and Namibia are the MEFMI countries that peg their currencies to the South African Rand under the Common Monetary Area (CMA).The CMA arrangement has its roots in a de facto currency union. In 1921, after the establishment of the South African Reserve Bank (SARB), the South African currency became effectively the sole medium of exchange and legal tender in South Africa, Bechuanaland (now Botswana), Lesotho, Namibia, and Swaziland. There were no internal restrictions on movements of funds within the area and virtually all external transactions were effected through banks in South Africa and subject to South African exchange controls. This situation continued after Botswana, Lesotho, and Swaziland gained political independence in the 1960s. Botswana, however, opted to withdraw in 1975 mainly because it wanted to retain the ability to formulate and implement its own monetary policy and to adjust the exchange rate, in response to shocks affecting its economy. 2
Monetary targeting countries in the MEFMI region are Malawi, Kenya, Zambia, Tanzania, Mozambique and Rwanda. 3
Inflation targeting countries in Africa are South Africa and Ghana. Uganda is currently on an inflation‐lite targeting framework 7 had been associated with periods of poor inflation performance. In the United Kingdom and
Sweden, inflation targeting replaced failed exchange rate pegs Eden, (1997).
The instruments of monetary policy can broadly be classified into direct and indirect
instruments. According to Gidlow (1998), the indirect policies are actions taken by the central
bank whereby it achieves its monetary policy aims by encouraging market participants to take
particular actions in terms of their lending and borrowing behavior.
Direct methods of
monetary control are appealing for several reasons. They are perceived to be reliable, at least
initially, in controlling credit aggregates or both the distribution and the cost of credit. They are
relatively easy to implement and explain, and their direct fiscal costs are relatively low. They
are attractive to governments that want to channel credit to meet specific objectives. In
countries with very rudimentary and noncompetitive financial systems, direct controls may be
the only option until the institutional framework for indirect instruments has been developed.
In the late 1970s, industrial countries began the transition away from direct instruments4 of
monetary policy towards full reliance on indirect instruments. Direct instruments create
distortions, including financial repressions and promote financial disintermediation and fiscal
dominance. Indirect instruments, on the other hand, are more effective in today’s increasingly
open economic environment because they are market-oriented. There are three main types of
indirect instruments, i.e. open market operations, reserve requirements and central bank lending
4
Direct instruments are interest rate controls, credit ceilings and direct lending. Direct instruments became increasingly ineffective and irrelevant as money and financial markets developed and modernized. Direct instruments are preferred when information is scarce, bank supervision and legal structures are weak, financial markets are undeveloped, low market participation and when transmission of monetary policy is uncertain. They are relatively easy to implement and explain to politicians and the public with low direct fiscal costs. Direct instruments are market based instruments, they are effective and offer greater flexibility and encourage development and deepening of formal interbank markets. They rely on market forces and reinforce Central Bank independence. 8 facilities, while the most common direct instruments are interest rate controls, credit ceilings
and direct lending.
The transmission mechanism of monetary policy is therefore crucial and has been an area of
abundant economic research in many countries. Despite the importance of Kenya’s financial
role in East Africa, little analytical work has been done on the transmission mechanism of
monetary policy, which is essential to the appropriate design, management, and implementation
of monetary policy Cheng (2006). A number of scholars have however done a number of
empirical analysis on how a monetary policy shock, usually defined as a temporary and
exogenous rise in a short-term interest rate, affects output, prices, exchange rates, as well as
other key economic variables. Sims (1980) pioneered in this area using a vector autoregression
(VAR) analysis.
VARs explicitly recognize the simultaneity between monetary policy (such as an increase in
the short-term interest rate) and macroeconomic developments (such as changes in output,
prices, exchange rates), as well as the dependence of economic variables on monetary policy.
Examples of studies using VARs in advanced economies include Christiano, Eichenbaum, and
Evans (2000) for the United States, Kim and Roubini (2000) for industrial economies and
Angeloni, Kashyap and Mojon (2003) for the euro area. Applications to non-industrialized
economies include Gottchalk and Moore (2001) on Poland, Arnoštová and Hurník (2005) on
the Czech Republic, Dabla-Norris and Floerkemeier (2006) on Armenia, Cheng (2006) on
Kenya, and Bakradze and Billmeier(2007) on Georgia.
The paper gives a full description of the Central Bank of Kenya monetary policy operating
procedures with emphasis on the role of OMO followed by an analysis of the effectiveness
using a VAR analysis with a detailed criticism or shortcomings of the process. A detail on how
9 the Central Bank of Kenya has dealt with autonomous factors especially the political landscape
and its impact on monetary policy is provided. The results of the study will not only contribute
to the limited body of knowledge in this area but help shape policy in the region.
b) Monetary Policy and the Economy
Proceeding from the analysis of the money supply equation given below we can explain how a
central bank can influence monetary policy:
We know:
The desired path for money supply is derived as:
WhereM = money supply; Y = real GDP; P = prices; V=Velocity;
The path for reserve money is approached from
where m = money multiplier.
A central bank can therefore manage the money supply–that is, conduct monetary policy, in
three ways namely by changing the monetary base through open market operations, by
changing the monetary base through discount lending and by changing the money multiplier by
changing the required reserve ratio.
Monetary base can be split into two:
MBn : non-borrowed monetary base or reserves - one that the central bank can control
completely
BR: borrowed monetary base or reserves - another that is less tightly controlled
Thus, MB = MBn + BR or MBn = MB-BR
10 MBn is tied to OMO –the Ms is positively related to MBn
Open market operations are by far the most effective tool for monetary policy implementation.
Open market operations apart from having the advantage of being under the direct and
complete control of a central bank, the transactions can also be large or small and they can
easily be reversed and implemented quickly. Most scholars and conventional academic
literature has placed a heavy, if not exclusive, emphasis on open market operations as the
means through which interest rates are influenced.
A central bank can also affect the volume of discount loans by setting the discount rate. A
higher discount rate makes discount borrowing less attractive to banks and will therefore
reduce the volume of discount loans. A lower discount rate makes discount borrowing more
attractive to banks and will therefore increase the volume of discount loans. Discount window
operations acts as a lender of last resort. Changes in reserve requirements5 affect the money
multiplier. By affecting the money multiplier, changes in the required reserve ratio can lead to
changes in the money supply. Frequent changes in reserve requirements can cause problems for
banks by making liquidity management more difficult. Other instruments that influence money
supply include forex sales and purchases, moral suasion, outright sales and purchase of
government securities and bank rate.
c) Monetary Policy Transmission Mechanism
Monetary policy effectiveness greatly depends on the stage of development of the economy, its depth
and the stability of the financial markets. Monetary policy changes are more quickly and closely
5
Reserves averaging are possible, it is a good but not best way to smooth fluctuations in short‐term interest rates, and by spillover, to the rest of the yield curve, as their effects are not clear over the medium term. 11 translated into changes in market interest rates and other financial prices if the financial system is well
diversified in terms of its institutions and products. Efficiency of the payments system, the level and
quality of data and the communication facilities in place also influence the effectiveness of monetary
policy. A sound financial sector not only fosters economic growth by mobilizing resources for
investment, but also provides a framework for undertaking effective monetary policy. Problems and
inefficiencies in financial systems can reduce the effectiveness of monetary policy, deepen or prolong
economic downturns, and, in case of large scale problems, trigger capital flight (Were, 2012).
The effectiveness of monetary policy is also greatly undermined by political interference, fiscal
dominance and poor legal environments (Nnanna, 2001). It is therefore imperative that
monetary authorities operate in an environment with appropriate legal frameworks, conducive
political climate and institutional structures that allow for autonomy. Furthermore, fiscal and
monetary policies should be complementary and should ensure consistency with the overall
goal for an economy.
d) Kenya’s Monetary Policy Profile
The conduct of monetary policy in Kenya after independence may be described as mainly
passive because no intervention was necessary in an environment of 8% GDP growth and
below 2% inflation rate, (Kinyua, 2001). In 1973, Kenya experienced the first major
macroeconomic imbalance with the oil shocks of 1973 followed by the coffee boom of
1977/78. The fixed exchange rate system had just collapsed with the Bretton Woods System in
1971. In these first two decades, monetary policy was conducted through direct tools which
were cash reserve ratio, liquidity ratio, credit ceilings for commercial banks, and interest rate
controls. The 1990s witnessed a steady decline in development with reductions in development
assistance occasioned by a perception of poor governance and mismanagement of public
resources (Putunoi and Mutuku, 2013).
12 In 1993, the Government of Kenya began a major program of economic reform and
liberalization. As part of this program, the government eliminated price controls and import
licensing, removed foreign exchange controls, privatized a range of publicly owned companies,
reduced the number of civil servants, and introduced conservative fiscal and monetary policies.
This ushered in a new era in monetary policy where open market operations (OMO) became
the main tool. The period was characterized by high interest rates and widening interest
spreads, which inhibited the benefits of flexible interest rate policy such as increasing financial
savings and reducing cost of capital. Competing against double digit inflation rate spurred on
by excessive money supply and accommodation of troubled banks, CBK used indirect tools to
tame inflation in an atmosphere of instability and extreme uncertainty.
In 1996, the CBK Act was amended and this allowed the CBK to shift from targeting broad
money M3 to targeting broader money M3x as the principal concept of money stock (Kenya,
2001). The CBK operates under a monetary policy programming framework that includes
monetary aggregates (liquidity and credit) targets that are consistent with a given level of
inflation and economic growth, (KIPPRA, 2006).
In 2007, Kenya experienced political turmoil from a disputed election. This affected the
economy negatively with growth dropping from 7.1% in 2007 to 1.6% the following year.
Again, in 2011 the Kenya shilling depreciated to its lowest point ever against the US dollar at
Kes107. The impact of the drought conditions in 2011, and the political crisis in the Middle
East and North Africa which was reflected in world oil prices were major contributors to the
13 exchange rate6 volatility and inflationary pressures in the period. In addition, the sovereign debt
crisis in Greece escalated with contagion effects in several major economies in the Euro zone.
The turbulence in the global financial markets was exacerbated by the US debt crisis which
resulted in the downgrading of US credit ratings in mid-2011. The situation was however
corrected through monetary policy tightening, moral suasion and intervention on the foreign
exchange market. This came at a cost as it slowed down the economic growth along weaker
global demand.
Kenya entered 2013 on an improving macroeconomic position as inflation had been contained
within single digits and the exchange rate stabilized. According to Vision 2030, Kenya’s
targeted GDP growth rate was 10% per annum starting 2012. It also wanted to keep interest
rates low for as long as possible to stimulate growth through access to credit facilities amongst
industries and households. According to World Bank, Kenya has the potential to be one of
Africa’s best performing economies.
6
Kenya has a managed‐float exchange rate regime. Foreign operations have not been geared towards managing domestic liquidity. 14 Chart I: Short term interest rates in Kenya 2008 - 2012
Source: Central Bank of Kenya
Chart II shows short term interest rates in the Kenyan economy from 2008 to Jan 2012. The 91
day Treasury bill rate, interbank rate and Repo rate track movements of the policy rate i.e. the
Central Bank of Kenya rate (CBR). The interbank rate is an overnight rate for uncollateralized
lending obligation among commercial banks.
Chart II: OMO and the Interbank Money Market
Source: Central Bank of Kenya
15 The CBK into 2013 developed a corridor to monitor volatility in the interbank rate. The
corridor is ±2.5% on the policy rate. Wide spreads of the interbank rate indicates distortions on
price discovery.
e) Tools of Monetary Policy in Kenya
The introduction of indirect methods of monetary policy in most developing countries has been
gradual. Kenya introduced OMO in 1990 while South Africa was earlier in 1989 with the other
countries following quite closely. Thus, open market operations have become the central
banks’ main instruments in the conduct of monetary policy Quintyn (1994).
(i) Open Market Operations
With the advent of liberalization, the most commonly used tool of monetary policy
implementation is Open Market Operations (OMO). These are executed at the initiative of the
central bank and aim at changing the central bank’s balance sheet and ultimately influencing
the conditions in the financial markets. The central bank therefore sells or buys treasury bills or
its own securities to commercial banks with the aim of influencing the level of liquidity in the
financial system. The principle therefore is to sell securities in order to sterilize any excess
liquidity in the financial system and conversely buys the same when pursuing a more liberal
monetary policy stance of providing credit to the banking system.
(ii) Reserve Requirements
Reserve requirements are the amount of funds that a depository institution must hold in reserve
with the central bank against specified deposit liabilities mainly for three main reasons:
prudential, monetary control and liquidity management. Reserve requirement therefore has an
16 element of control in that it is administratively determined by the monetary authority, but is
also an indirect method of influencing liquidity through management of the central bank’s
balance sheet. Studies have shown that there is a general downward adjustment of the ratio
among most countries. However; many countries have retained reserve requirements as part of
their monetary policy instruments even where open market operations are not necessarily
constrained.
Kenya uses the averaging system of reserve requirement over a 14-day cycle. Banks have to
meet a certain balance in the middle of the month and at the end of the maintenance period.
The ratio is determined as the average amount of deposits and liabilities of a bank with the
central bank during that period. When monetary authorities have decided to have reserve
requirements as part of their monetary policy framework, the key elements to be observed
include: (i) the level and frequency of change of the reserve requirements; (ii) the maintenance
period; (iii) the liabilities subject to the requirements; (iv) the eligible assets for meeting the
requirement; (v) incentive/ remuneration (if any) structure for compliance; and (vii)
synchronization with the other instruments of monetary policy.
As countries adopt more market oriented instruments, reserve requirements should not be
changed frequently as they are not flexible instruments of liquidity management. Frequent
changes would be disruptive to banks as it takes time for them to adjust in order to reflect these
changes. Most MEFMI member countries have conformed to this except for Zambia and
Zimbabwe where reserve requirement ratios have changed frequently, all the other countries
have changed less often.
In most MEFMI countries, the types of liabilities subject to the requirement are commercial
banks’ demand, time and savings deposits. However, in Zimbabwe reserve requirement was
17 extended to other financial institutions such as finance houses in an attempt to rein in reserves
and try to salvage monetary policy (Mabika, 2001). The statutory reserve requirements were
removed on 28th July 2010 (Mid-Year monetary policy statement By Dr. Gideon Gono,
Governor, Reserve Bank of Zimbabwe).
(iv) Standing facilities
These are the monetary policy instruments which may be used at the commercial banks’ own
initiative, to access liquidity from the central bank. When used as refinancing facility, standing
facilities are normally categorized as “the lender of last resort”. Under indirect monetary policy
management, these facilities could be used by the central bank to limit interest rate volatility by
setting a boundary for short-term market rates. The performance of these functions together
with their proper design to efficiently support the other monetary policy instruments depends
on the stage of development of money markets, the level of competition in the securities
markets and the soundness and competition of the banking system. Whatever function is
allotted to the facility; central banks ought to retain discretion in their use to maintain overall
control.
(V) Discount window
This is where banks can come for accommodation from the central bank in case of reserve
shortfall. In order to encourage secondary market activity, some central banks set punitive
interest rates at which commercial banks can access this window. In Kenya the rate is the
Central Bank Rate (CBR) plus a punitive rate. This has entailed a policy change from the
previous rate that was 3 percentage points above the latest rate on the 91-day Treasury bill rate.
Hence, the high rate acts as a deterrent to banks to initially source for funds from the market
before resorting to central bank for accommodation.
18 1.1.
PROBLEM STATEMENT
With more countries moving away from direct controls towards market-oriented methods of
implementing monetary policy, interest has increased in the operating procedure for open
market operations. The attractiveness of OMO is embedded in the fact that they are flexible
tools, which makes them very powerful in the conduct of monetary policy (Akhtar, 1997). The
CBK implements monetary policy mainly through OMO. The other tools used occasionally are
discount window operations, reserves requirements and moral suasion.
For open market operations to be conducted efficiently as is the case in most developed
countries, a well-developed financial market is necessary. This is however a complex process
that requires substantial infrastructure and sophisticated legal and regulatory framework
(Enoch, 1996). Ikhide (1998) mentions an intricate relationship between financial sector
reforms and the objectives, instruments and operating procedures of monetary policy. More
importantly, indirect monetary management will only succeed when substantial reforms are
implemented in the financial sector whose reforms include reduction in the size of government
deficit, which strains many economies in transition.
Axilrod (1995) suggests that for OMO type of operations to be effective, they require
supportive changes in other policy instruments such as reserve requirements in addition to
having a competitive banking system and a well-developed securities market. This calls fora
well-functioning primary market where the central bank auctions treasury bills or its own
securities and an active secondary market where the securities can be traded.
Financial markets are important for monetary policy for at least three reasons: firstly, the
desired stance of policy is achieved by the central bank operations in these markets; secondly,
19 financial markets are the channel through which the effects of policy are most immediately
transmitted; and, thirdly, they provide feedback to policy makers – financial markets contain
information that is of value to central banks in considering monetary policy.
1.2.
JUSTIFICATION
Despite the prominence given to monetary policy in most MEFMI member countries, the
process of attaining macroeconomic objectives and testing the transmission of monetary policy
have not been extensively studied. In fact, the uncertainties about the instruments have
constituted drawbacks in the effective implementation of monetary policy.
Roe and Sowa (1997) suggest that descriptive papers are lacking in the MEFMI region on the
manner in which monetary control is conducted. Whilst, some countries are far behind, others
have developed their markets and they have even chosen to diversity their instruments in the
desire to make transmission more effective.
This paper makes three contributions in attempting to test the efficacy of using open market
operations in monetary policy implementation in Kenya:
I.
Provide an exhaustive and critical review of the existing monetary policy
implementation tools in the Kenyan economy.
II.
Apply time series econometrics to study the specific variables. The paper will examine
the impact of a monetary policy shock on output, prices and the real effective exchange rate
using techniques commonly used in the Vector Autoregressive (VAR) literature.
20 III.
The study will inform policy in this area and will attempt to fill the knowledge gap that
currently exists.
1.3.
OBJECTIVE OF THE STUDY
Today there is consensus that the central bank must act in a systematic way. Its policy decisions
and the process that leads to them must be transparent so that the private sector can understand
and anticipate the policy (Woodford, 2003). Credibility is therefore the cornerstone of a
monetary policy that aspires to achieve optimal macroeconomic results (Cukierman, 1992).
Credibility can be gained by a convincing track record. But to sustain its credibility, the central
bank must commit itself to a policy that delivers on its goal.
Central banks have the ability to change money supply and to shape the expectations of market
participants through open market operations. The objective of this study is to examine the
effectiveness of open market operations as an indirect tool of monetary policy implementation
in Kenya. This will be through:
1.
Full description of the financial markets developments and instruments of monetary
policy in Kenya.
2.
Detailed examination of the monetary policy operating procedures with emphasizes on
the role of OMO
3.
Analysis of the effectiveness of open market operations on monetary aggregates, price
levels and exchange rate using econometric techniques.
21 1.4.
RESEARCH HYPOTHESIS
To meet the above objectives the following hypotheses will be tested:
H1: Open market operations has no effect on price level
H2: Open market operations has no effect on the exchange rate
1.5.
LITERATURE REVIEW
A large part of the empirical literature on monetary transmission uses vector autoregression
analysis (VARs). In VARs it is the response of variables to exogenous policy actions that one
needs to examine in order to estimate the effects of monetary policy on the economy 1998,
(Rude Busch). Isolating the economic effects of monetary policy shocks, however, is not
straightforward as the response of economic variables to monetary policy impulses reflects the
combined effect of the policy actions and of the variables to which policy responds (Christiano
et al., 1996). This identification problem is addressed with the imposition of a number of
identifying restrictions based on economic theory.
Despite the importance of Kenya’s financial sector role in East Africa, relatively little
analytical work has been done on the transmission mechanism of monetary policy, which is
essential to the appropriate design, management, and implementation of monetary policy. The
transmission mechanism of monetary policy has been an area of abundant economic research in
many countries. A prominent recent trend in this field has been the empirical analysis of how a
monetary policy shock, usually defined as a temporary and exogenous rise in a short-term
interest rate, affects output, prices, exchange rates, as well as other key economic variables.
Typically, this strand of research has been conducted in the context of a vector autoregression
(VAR) framework pioneered by Sims (1980).
22 Durevall and Ndung’u (1997), using Kenyan data during 1974–1996, find that exchange rates,
foreign prices, and terms of trade have long-term effects on prices, while interest rates and
money supply have short-term effects.
Brischetto A and Graham (1999) examined the effects of monetary policy in Australia using a
small structural vector autoregression model. The model they used is a modification of the
small open economy model developed for the G6 economies (the G7 less the United States) by
Kim and Roubini (1999). Consistent with Kim and Roubini, they find no evidence of the price
or exchange rate puzzles identified in the literature. They found that monetary policy shocks
have a delayed and gradual effect on the price level and a small temporary effect on output.
Morsink and Bayoumi (2001) used VAR models with quarterly, seasonally-adjusted data from
1980Q1 to 1998Q3, using two lags to analyze the effect of monetary shock on the Japan
economy. In their basic model, they used economic activity, prices, interest rates, and broad
money. They found that both interest rate and broad money significantly affect output. Then,
after examining the basic model, they extended the VAR to examine different channels of the
monetary transmission mechanism and concluded that both monetary policy and banks’
balance sheets are important sources of shocks to output, that banks play a crucial role in
transmitting monetary shocks to economic activity, and that business investment is especially
sensitive to monetary shocks.
Aron and Muellbauer (2002) used multi-step models to study inflation and output in South
Africa and find an important link between interest rates and output and that low inflation is
associated with higher openness of the economy, low wholesale prices relative to consumer
23 prices, high real exchange rate, low real mortgage payments, low real interest rates, low output
gap, as well as low indirect tax rate.
In their analysis, Disyatat and Vongsinsirikul (2003) also used the VAR approach with
quarterly, seasonally-adjusted data from 1993Q1 to 2001Q4 with two lags to analyze the
monetary transmission mechanism in Thailand. Their basic model included real output, price
level, and the fourteen-day repurchase rate, which they assumed to be the measure of monetary
policy. They found that tightening monetary policy led to a decrease in output, which bottomed
out after around 4–5 quarters and dissipated after approximately eleven quarters. The aggregate
price level initially responded very little, but ultimately started to decline after about a year.
Investment appeared to be the most sensitive component of gross domestic product (GDP) to
monetary policy shocks. Their findings were consistent with those of other countries and with
what monetary theory suggests.
Saxegaard (2006) uses a threshold vector autoregression model for a number of sub-Saharan
African countries and finds that excess liquidity in the region weakens the monetary
transmission mechanism and thus the ability of monetary authorities to influence demand
conditions in the economy.
Cheng (2006) examined the impact of a monetary policy shock on output, prices, and the
nominal effective exchange rate for Kenya using data during 1997–2005. Based on techniques
commonly used in the vector autoregression literature, the main results suggest that an
exogenous increase in the short-term interest rate tends to be followed by a decline in prices
and appreciation in the nominal exchange rate, but has insignificant impact on output. 24 Mohsin K (2010) also carried out a cross-county study of Sub Saharan Africa (SSA) countries
and found a close correlation between the growth of GDP and the growth of credit. These
correlations over the period 1991-2007 are reported for 20 SSA countries for which data was
available in both nominal and real terms7.
Tsangarides C (2010) used a VAR analysis to assess the transmission mechanism of monetary
policy on output and prices for Mauritius, using data for 1999–2009. The results show that an
unexpected monetary policy tightening—an increase in the Bank of Mauritius policy interest
rate—leads to a decline in prices and output but the effect on output is weaker.
7
Two specific credit variables were used for the correlations‐total domestic credit extended by banks, which includes credit both to the government and the private sector, and credit to the private sector. 25 CHAPTER 2
2.
FINANCIAL MARKETS DEVELOPMENT AND MONETARY
POLICY IMPLEMENTATION
2.1.
Introduction
Financial markets are central to the conduct of monetary policy, as monetary policy is
implemented largely through operations in these markets. The effectiveness of the transmission
of monetary policy to the real economy hinges crucially on a set of parameters that are affected
by the structure of the financial system; that is, the existence and degree of development of
financial markets and changes in these markets that affect their functioning.8
The objective of financial markets development is to increase financial resources available to
the economy and to enable more efficient use of resources. This improved management of
resources stimulates and accelerates the process of economic growth. Through the increase in
the range of financial instruments available to savers and investors, lead to increased
competition in the financial system and thus help in channeling resources to where they yield
highest returns according to Popiel (1990).
One of the goals of monetary policy which central banks have come to focus on lately is the
Stability of financial markets. Hence central Banks emphasize the promotion of more stable
financial markets. Financial crisis inhibit the ability of financial firms to channel funds to
productive investment opportunities. It is not just about financial markets development but
8
Krause and Rioja(2006)empirically analyzed how financial development is related to monetary policy for37countries. Results suggest that more developed financial markets significantly contribute towards explaining more efficient policy implementation (controlling for central bank independence, inflation and targeting membership in the European Monetary Union). 26 also financial markets stability. This is why many central banks now have a department of
financial stability.
Literature provides five main channels in the monetary transmission mechanism namely
interest rate or money channel, the credit channel, the exchange rate channel, the asset price or
wealth channel and the most recent addition to the literature, the expectations channel. The
transmission of monetary policy through the interest rate mechanism operates through its
impact on the cost of capital, affecting both businesses’ and households’ investments and
spending decisions. Taylor (1995) takes the position that there are strong interest rate effects on
consumer and investment spending, and hence a strong interest rate channel of monetary
policy.
The role of credit channels arises from the problem of asymmetric information and costly
enforcement of contracts, which creates agency problems in financial markets. Because of this,
banks are viewed as playing a special role in the financial system, and hence give rise to the
importance of the credit markets in transmitting monetary policy. Two important channels
under the credit view are the bank lending channel and the balance sheet channel.
With growing openness of an economy, the exchange rate may also play an important role in
imparting monetary policy changes through its impact on net exports and aggregate demand.
Parallel to central banks’ move of adopting a single interest rate as the policy interest rate to
signal monetary policy changes, increasing attention is now also being paid to the expectations
channel of monetary policy. This is because changes in official interest rates can influence
expectations about the future course of real activity in the economy.
27 2.2.
FINANCIAL MARKETS DEVELOPMENTS Experience from industrialized countries has shown that a phased type of reform in the
financial markets would initially start with elimination of credit ceilings. This should be
gradual and would involve allowing a wider range for deposits and lending rates, or steadily
adjusting minimum deposit rates and maximum lending rates. This would enable the objectives
of effective resource mobilization and allocation by promoting flexibility in interest rate
determination and allocation of credit. Eventually, the development of money markets and
promotion of competitive financial systems for the strengthening of monetary control and
interest rate mechanism would follow.
A proxy that is generally used to measure financial sector development is the ratio of broad
money (M2/M3) to GDP, which shows the level of monetization in the economy. This view is
inspired by the work of (Levine, 1997). Thus, as financial development takes place; the ratio is
expected to rise. In Kenya the ratio was 37.9 percent in 1980 then rose to around 50 percent in
1994 and is currently at 40 percent.
The spread between lending and deposit rates is the other measure of financial development.
Since financial liberalization entails the use of indirect instruments in the central banks’
liquidity management, this is in turn supposed to cause the lending-deposit rate spreads to
narrow and consequently reduce the cost of intermediation. Therefore as efficiency improves
and competition within the financial system increases, the interest rate spreads are expected to
narrow (Alexander, Balino & Enoch , 1996).
28 2.1.1 Financial liberalization
While there is continued debate on the extent, speed and sequencing of financial liberalization,
seems to be a consensus that a more liberalized financial system is desirable and leads to
greater efficiency of financial intermediation. For more than a decade now, financial
liberalization in developing countries has been cited as a necessary and significant part of an
economic policy package. Typically, financial sector liberalization in developing countries has
been associated with measures that are designed to make the central bank more independent,
relieve “financial repression” by freeing interest rates and allowing financial innovation, and
reduce directed and subsidized credit, as well as allow greater freedom in terms of external
flows of capital in various forms.
2.1.2 Interest rate deregulation
The most important aspect of financial liberalization from the perspective of the transmission
of monetary policy is the deregulation of interest rates. In principle, the removal of prescribed
interest rates and interest rate ceilings allows policy rates to be transmitted to retail interest
rates more quickly and to a larger degree, increasing the role of the interest rate channel.
Financial liberalization promoted the emergence of new financial products and this gave rise to
problems of measuring money, creating problems in estimating a stable money demand
function9.
A stable money demand model is essential for the functioning of the interest rate/money
channel as it helps to ensure that the pass-through is predictable, stable and efficient. Instability
9
A stable money demand function is generally considered essential for the formulation and conduct of efficient monetary policy as it enables a policy‐driven change in monetary aggregates to have a predictable influence on output, interest rates and ultimately price (Sriram, 2001). Sichei and Kamau (2012), analyse demand for different monetary aggregates (M0, M1, M2 and M3) in Kenya for the period 1997‐2011. The demand for money functions is found to be unstable over the period for the parameter values, implying that the current monetary targeting policy framework in Kenya is inappropriate. 29 in the money demand models of most countries, plagued with the measurement problems of
monetary aggregates, shifted central banks’ focus from targeting money supply to targeting a
specific interest rate.
2.1. 3 Capital account liberalization
Increased capital account liberalization has brought about greater cross border capital flows.
Financial sectors worldwide have not only witnessed greater volatility in exchange rates and
liquidity arising from these flows, but have also experienced cross border financial
consolidations and financial market integration. Greater financial market integration often
induces an increase in market competition and this will have an impact on monetary
transmission. In this case, de Bondt (2002, 2005) examines the pass-through of changes in the
policy rate to bank deposits and lending rates in the Euro Area. Using the Error Correction
Model (ECM) and Vector Autoregression (VAR), he finds a quicker retail interest rate pass
through after the introduction of a common monetary policy in 1999.
Sander and Kleimeier (2004) also find that financial integration in the Euro Area has produced
more competitive markets that improve the pass-through to deposit rates. Similar results are
also found by Carlino and DeFina (1998), Heinemann and Schüler (2002), Kwapil and Scharler
(2006), Sorensen and Werner (2006) and Chionis and Leon (2005).
2.1.4 Central bank independence
In recent years, many countries have made progress in removing their central banks from
government control that is, making them independent. As a broad generalization, interest in
30 central bank independence (CBI) was motivated by the belief that, if a central bank was free of
direct political pressure, it would achieve lower and more stable inflation10.
CBI may also be viewed from the interaction of the government and the Central Bank. In the
context of the relationship of fiscal and monetary authorities there is a strong belief that the
more independent the central bank is, the less the monetary authorities can be forced to finance
deficits by creating money Eijffinger and Haan(1996).
CI is a necessary condition for
effective monetary policy implementation. The concept of an independent central bank was
recognized as a “good practice” that contributes to the better control of inflation and most
countries try to improve the independence of their central banks in order to maintain stability.
The central bank independence is more often analyzed together with its accountability Olena
(2010).
2.1.5 Financial disintermediation
Schmidt et al (1997) discuss the theoretical underpinnings of financial intermediation.
According to them, based on theories by Townsend (1979), Diamond and Dybvig (1983),
Diamond (1984) and others, banking institutions are a special type of intermediary that, under
specific conditions, can solve specific information and incentive problems in the relationships
between savers and borrowers better than other financial market players. This is the reason for
the importance of banks as financial intermediaries, and it thus underscores banking
institutions’ role in transmitting monetary policy impulses. It also implies that changes in the
nature of financial intermediation may have important implications for the operation of the
monetary transmission mechanism.
10
See (Cukierman, et al., 2002; Cukierman, Webb, & Neyapti, 1992; Eijffinger & Haan, 1996; Polillo & Guillen, 2005; Schwödiauer, et al., December 2006 ) 31 For example, by Mojon (2000), de Bondt (2002), Sorensen and Werner (2006) and Gropp et al
(2007); these studies not only examine the dynamic pass-through between market interest rates
and retail rates in the Euro Area as a function of the degree of financial market competition but
also analyze a host of other structural differences in the financial systems. . Monetary policy in
general influences retail prices. A tightening bias contacts money supply and pushes interest
rates upwards and vice versa.
2.1.6 Financial innovations
A component of development of the capital markets is the increase in innovations in the
financial sector. Tufano (2002) broadly categorizes financial innovations into two types,
product and process innovations. Product innovation can be illustrated by corporate securities
or derivative contracts, while process innovation can be demonstrated by new means of
distributing securities, processing transactions or payment system technologies.
Nyamongo and Ndirangu (2013) analyzed the impact of financial innovation in the banking
sector on the conduct of monetary policy in Kenya during 1998-2012. The study focuses on
whether the wave of financial innovations in Kenya has impacted on the transmission
mechanism of monetary policy. The results show that the innovations have improved the
monetary policy environment in Kenya as the proportion of the unbanked population has
declined coupled with gradual reduction in currency outside banks. The period post 2007 when
the country has experienced the fastest pace of financial innovation is associated with
instability in the money multiplier, income velocity of money and the money demand.
However, recent trends point towards stabilization pointing to the need for further examination
to establish whether indeed the break in trend is of structural or transitory in nature.
32 2.1.7 Financial consolidations
The 1990s saw a strong wave of financial consolidation in financial sectors across the globe.
Recent financial consolidation has been driven mainly by technological factors, deregulation
and globalization, as well as by the responses formulated by policymakers to resolve
weaknesses in their financial systems. Greater financial consolidation might change the
economic and financial environment in which monetary policy decisions are made, and thus it
could also affect policy transmission. Financial consolidation may lead to a decreasing number
of counterparties for monetary operations, thus reducing competition.
Moreover, financial firms in a less competitive financial sector generally have greater power of
discretion in terms of adjusting prices to changes in costs. Empirical studies by Hannan and
Berger (1991) and Neumark and Sharpe (1992) support this view, as they find that interest rate
rigidity is significantly greater in markets characterized by higher levels of concentration.
However, if financial consolidation led to the creation of large and strong banks, the resulting
outcome would differ because larger institutions, often operating in several markets, may
promote a faster arbitrage of interest rate changes across markets and assets, hence resulting in
an improvement in the degree and speed of pass-through.
As shown by Cottarelli and Kourelis (1994), the existence of large and strong banks operating
in a competitive environment enhances pass-through. Therefore, the impact of financial
consolidation on the pass-through of the policy interest rate to money market and retail interest
rates is highly dependent on the competitive environment it creates. If it leads to increased
competition, then pass-through is more efficient.
The Kenyan banking sector is often seen as highly oligopolistic with remarkable features of
33 market concentration and leadership; it is also characterized by small-sized fringe banks with
very high overhead costs and weak capital bases. The capital levels of most of the banks used
to be below $25m
The Government of Kenya, through the Finance Act, 2008, begun
increasing minimum capital requirements for banks from Kshs 250m ($3.1m) to Kshs 1bn
($12.5) by 2012. Critically, however, the impact of consolidation on efficiency, stability and
access will depend on the implications of a more concentrated banking system for competition,
Beck (2009).
2.1.8 Payment Instrument Technology
Financial markets have undergone rapid technological change over the last two decades, and
nowhere are this more obvious than in the emergence of new payment technologies. The
existence of Automated Teller Machines (ATMs) and electronic money (e-money) economizes
holdings of cash, while cheques and debit and credit cards represent alternative and more
convenient modes of payment that affect the velocity of money. Arnon and Bandiera (2004)
discussed the issues pertaining to electronic money, central banks’ operations and monetary
policy effectiveness. They conclude that as long as central banks continue to operate and retain
control over short-term interest rates and money supply is used only as an information variable,
the impact of digital money on monetary transmission is unlikely to be of concern.
The usage of credit cards allows greater consumption smoothing and to some extent boosts
spending. To the extent that the pass-through to credit card rates is large and quick, the impact
of monetary policy actions on consumption and spending will be significant. On the other hand,
as credit cards provide a form of financing, akin to a personal loan, interest rate changes due to
monetary policy will have a lesser income effect on households as credit cards can be used to
34 cushion this impact. Nevertheless, as these developments are relatively recent, there is a dearth
of empirical studies examining these issues, and thus the above arguments remain conjectural.
2.1.9 Islamic finance
A study by Bank Negara Malaysia in 2006 suggests that the pass-through from policy rates to
the Islamic money market is fast and sizeable and consistent with those of conventional
estimates. In addition, the study finds that profit rates follow conventional money market rates
closely, reflecting the evidence of arbitraging between the two markets. As such, as long as
there is institutional arbitraging between the two markets, the transmission of monetary policy
will be effective through the Islamic and conventional financial sectors.
The Islamic or Shariah-compliant11 banking is a growing segment of the financial sector in
Kenya. Islamic banking was introduced in 2008 when the first two Islamic Banks, Community
Bank (FCB) and Gulf African Bank (GAB), opened their doors. Thereafter, Islamic finance has
spread slowly into insurance, investments, and pension sectors.
Current market surveys indicate that a large section of the Muslim community remains
untapped by the banking industry due to either non availability of riba-free12 (interest-free)
banking or low incomes. Notwithstanding, Islamic banks in Kenya do not participate in the
OMO market which has implications for monetary policy. The CBK and the government has
11 Shariah Law is the moral code and religious law of Islam, described as the infallible law of God. It deals with
crime, politics, economics, and personal matters (Bashir 1999). A Shariah compliant product meets the
requirements of the Islamic law. Shariah compliant products enable market players to perform similar functions as
in conventional markets, but with the exception that the instruments used to perform these functions must be based
on Shariah laws and principles.
12 Riba (interest) is prohibited in Islam. The modern banking system is organized on the basis of a fixed payment
called interest. To charge interest from someone who is constrained to borrow to meet his essential consumption
requirement is considered an exploitative practice in Islam. It instead promotes the concept of profit sharing.
35 the challenge of amending the necessary sections of the Banking Act and Prudential Guidelines
to reflect this new reality.
2.3 Summary
The objective of this section was to determine how the monetary transmission mechanism is
affected by financial market developments. The study is motivated by the fact that the Kenyan
financial system has undergone tremendous change in the last decade and that the pace of
change is only likely to accelerate in the coming decade. These changes have important
implications for the effectiveness of monetary policy. The effectiveness of monetary policy in
affecting economic activity and inflation depends on the state of the financial system, and
various financial developments can potentially change the way monetary policy is transmitted
through the financial system
36 CHAPTER 3
3.
MONETARY POLICY FRAMEWORK AND PROCEDURES
3.1.
Introduction
Kenya pursues a monetary aggregates targeting framework to achieve its inflation objective13.
The framework has remained fairly the same over time with the CBK continuously refining
monetary policy operations and procedures to enhance efficiency and effectiveness in a
changing financial and economic environment. In formulating monetary programs, the Bank
starts with estimating the money demand consistent with the target rate of inflation and GDP
growth. This forms the basis for setting desired path for monetary growth to which actual
money supply has to conform during policy implementation stage. This however changed in
2011 as target variables became unstable and targeting short term interest with the introduction
of an interest rate corridor came to the fore in a monetary policy framework that is more of
inflation targeting-lite
The rest of the chapter is organized as follows; section I outlines the general framework of
monetary policy for Kenya and section II discusses the current operational procedures in place.
13
Kenya is currently on an inflation targeting framework. It announces the target inflation and explains the minister of finance if this target is not realized 37 3.2. Monetary Policy Framework for Kenya
Fig3.1 IMPLEMENTATION OF MONETARY POLICY
TOOLS OPERATING TARGET Source: Author,(2015)INTERMEDIATE TARGET GOALS OMO
RESERVE MONEY/OVERNIGHT RATE MONEY SUPPLY
INFLATION
Central banks cannot determine directly the rate of monetary expansion. This depends on a
multitude of factors outside the immediate sphere of influence of a central bank. This makes
the monetary authorities to identify yet another intermediate target: the interest rate or
monetary base. Once the link between the monetary base and the money supply is understood,
a strong positive correlation between the evolution of the money supply and that of prices is
postulated. This correlation is not always straightforward, because it depends on the stability
and predictability of velocity, and, ultimately, on money demand (Nyamongo and Ndirangu,
2013).
In 2007, the Central Bank of Kenya Act was amended to allow the formation of the Monetary
Policy Committee (MPC). The Committee is charged with the responsibility of formulating
monetary policy. The MPC meets every sixty days, unless the macroeconomic environment
necessitates more frequent meetings. The Committee meets to review the macroeconomic
environment on the basis of which a decision is made on the monetary policy stance. The
monetary policy stance is communicated through the CBR.
38 The key tools that the CBK uses to implement monetary policy are:
1.
Open Market Operations (OMO) -the bank relies heavily on this instrument.
2.
Reserve Requirements- currently 4.5 percent. This is not very active.
3.
Other Instruments—these include rediscount facilities and lender of last resort facility
which is also not very popular.
Monetary targeting framework has served the country well with refinement of operations and
procedures to enhance effectiveness. The surge in inflation in early 1990s to about 70 percent
(the time of the first multiparty elections in 1992) led to amendment of the CBK Act in 1996 to
give CBK more autonomy to manage monetary policy. Over time, appropriate monetary policy
has kept inflation at satisfactory levels except for occasional supply shocks.
3.3.
Forecasting Liquidity for Monetary Policy Operations
Liquidity forecasting is the process of estimating short term liquidity flows on the central bank
balance sheet. Monetary policy operational guidelines are based on comparison of daily
forecast of components of reserve money with their respective targets. The daily forecasts of
reserve money covers two categories of transactions i.e. those increasing and those reducing
liquidity.
The monetary policy operational committee (MPOC) therefore assesses the impact of these
transactions on reserve money with particular attention on the expected deviation of reserve
money from its target and in particular to the deviation in the total reserves of commercial
banks and NBFIs. If forecast bank reserves are in surplus, the central bank mops and injects
funds if the forecast indicates a deficit of cash in the market. A lot of discretion is exercised by
the monetary authorities when making this decision. Trends in the inter-bank overnight market,
39 developments in the exchange rate market as well as inflation expectations in the months ahead
are also considered in designing the intervention programme.
Operational Procedures
The MPOC prepares daily forecasts of reserve money by adjusting the previous day’s actual
closing position with expected liquidity injections and withdrawals for the day. The expected
sources of liquidity include:

Maturities of previous mop up arrangements with commercial banks

Any overnight loans to commercial banks

Central bank purchases of foreign exchange from the domestic market

Rediscounts of existing government securities by banks

Other government payments due
On the other hand, sources of liquidity withdrawal include:

Roll over of outstanding government treasury bills and bonds through the primary
auction and any additional borrowing through tap sales

Mop up of excess liquidity through sales of government securities by central bank such
as Repos

Maturities of loans due by commercial banks to the central bank

Income tax payments to government through commercial banks

Redemption of government securities previously rediscounted at the central bank and

Payments of government external debt.
In 1996, Kenya introduced repurchase agreements (repos) for purposes of monetary policy
implementation. On a daily basis the bank determines the excess or shortfall in the banking
40 system. Depending on the outcome, for the day the bank sells Government securities to
commercial banks at an agreed rate and repurchases the same on maturity plus interest.
The CBK advertises on Reuters the amount it intends to inject or mop up and commercial
banks send in their bids at competitive rates indicating the tenors and bid rate. The Bank
decides on a cut-off and advises the successful participants details include the exact discounted
amount that commercial banks will be debited with, the security they will receive in exchange
of funds and the repurchase date of the issued security. All repo transactions are on delivery
versus payment basis and all participating banks are expected to sign the Master Repurchase
Agreement (MRA) with central bank. Since Government securities are held in the Central
Depository accounts, the respective accounts are automatically updated once the transactions
are completed.
Information infrastructure at the Central Bank which issues government securities is not
directly linked to the Nairobi Stock Exchange (NSE) where bonds are traded. Despite the NSE
automating trading in August 2006, government bonds traded at the stock exchange are still
updated manually. This has greatly deterred trading of government securities and further
deepening of the financial markets.
3.4.
Monetary Policy Operating Procedures in Kenya
The CBK principal objective is formulation and implementation of monetary policy directed at
achieving and maintaining stability in the general level of prices (CBK 2010). The aim is to
achieve stable prices – that is low inflation and to sustain the value of the Kenya shilling. CBK
formulates and conducts monetary policy with the aim of keeping overall inflation at the
41 government target of 5 per cent (CBK 2010). Achieving and maintaining a low and stable
inflation rate together with adequate liquidity in the market facilitates higher levels of domestic
savings and private investment and therefore leads to improved economic growth, higher
incomes and increased employment opportunities.
The main target variables therefore for monetary policy are inflation and output. However, the
CBK cannot influence its target variables (inflation and output) directly. It influences them
indirectly using mainly two monetary policy instruments; interest rates which is the price of
liquidity and reserve money which is the quantity of liquidity. To influence the instruments, the
CBK uses a number of monetary policy tools that include open market operations, Central
Bank Rate, standing facilities (as a lender of last resort), required reserves, foreign market
operations and moral suasion.
Open market operations are flexible in the timing and volume of monetary operations and are
market-oriented and provide a means of avoiding the inefficiencies of direct controls. Whether
it adopts an active or a passive approach, the central bank should start by collecting figures on
the supply of and demand for bank reserves to inform decision making. As the single supplier
of central bank money, the central bank through altering its terms and availability can influence
the pricing and availability of wider money in line with its desired policy goals. Such goals are
usually laid out in the statute of the central bank and relate to monetary policy (and financial
stability).While non-central bank money, such as deposits and mobile phone payments may
form the majority of money circulating in an economy at a given time, ultimate settlement of
such transactions still occurs in central bank money.
42 While price stability is the ultimate goal of central bank policy, it is a medium term goal. In the
short-run the central bank may have little ability to control this variable. Often central banks
will have in addition an operational target. An operational target is an economic variable that
the central bank wants to and indeed can to a large extent control on a day-to-day basis. It is
also the variable that the decision making body of the central bank decides on and uses to
communicate the stance of policy and often a key part of the transmission mechanism of
monetary policy. The Interbank overnight rate is one of the operating targets of the CBK.
Chart III: OMO and Interbank Rate for Kenya 2014
Source: Author,(2015)
Chart IV, shows OMO and the interbank rate. The shaded are represent a corridor of plus or
minus 2.5%. As the overnight rate is confined to the corridor through OMO, a split over effect
is transmitted to other short term interest rates making them less volatile.
3.5.
The Process Flow for Open Market Operations
43 The monetary policy committee (MPC) of the CBK meets every two months and decides the
monetary policy stance. Within the bank there is a departmental committee that implements the
directives of MPC. The committee meets every day at 11.00am and analyzes the liquidity
forecasts for the day by observing key variables in the CBK balance sheet. Free reserves
provide greater insights on the liquidity conditions. Free reserves are composed of excess
reserves and voluntary reserves and greater discussions with the market provide insights in
decision making. Dealers from the central bank’s OMO desk should be continually speaking
with other traders in an effort to understand the factors influencing market conditions, enabling
policymakers to better assess market psychology.
Chart IV: Banks Voluntary and Excess Reserves
Source: Author,(2015)
Voluntary reserves are additional reserves held by commercial banks for precautionary
motives. Demand for voluntary reserves arises from a desire to self-insure and depends on
uncertainty of payment flows. Excess reserves on the other hand are reserves that exceed
commercial banks demand for them. The central bank will also require estimates of other
factors affecting reserve supply, such as government deposits, currency in circulation, foreign
44 exchange, and the float arising from timing differences between crediting and collecting funds
in the central bank clearing system.
A broadcast is therefore made through service providers such as Bloomberg and Reuters and
bids are received from 11.30am to 12.45pm. The auction method mostly used is the multiple
price auction technique. In a multiple-price auction, bids are ranked until the offer amount is
exhausted hence successful bidders pay their bid price. The multiple-price method could
enhance competition, since each bidder knows that he will pay the price offered and not the
minimum price at the auction. However, uncertainty in the multiple-price auction is one of the
biggest disadvantages. This arises from the bidder’s fear that he may pay above the market
price for the auction. In a developed and deep market, where price discovery is not a problem,
the element of uncertainty may be very small but where the market is less developed, prices
tend to be volatile and the element of uncertainty could be substantial.
Other auctions techniques that have also been used before are the single price auction and the
hybrid/Spanish auction. In a single price auction, bids are ranked and the stop-rate becomes the
interest rate applied to all successful bids. In a well developed and deep market, the single-price
auction attracts more bidders since it reduces the cost of collection of information and
stimulates potential investors to participate in auctions. However, the single-price auction
method creates the possibility of speculation by participants since knowing that they would pay
the lowest price, they place very high bids so as to crowd-out other participants.Under the
hybrid system, winning bidders pay their bid price if it is lower than the weighted average price
of winning bids, while all other winning bidders pay the weighted average of winning bids. The
price that a bidder has to pay depends on the bids of all other winning bidders, including his
own bids.
45 Successful bids are notified and confirmed through Reuters dealing. Banks on their part submit
messages to the back office that is charged with the responsibility of settlement.
46 4.0 DATA ANALYSIS AND PRESENTATION
4.
Introduction
This chapter contains the model set up, a detailed description of data and analysis and results
within the framework of the research objectives and hypothesis. Detailed analysis and a brief
discussion of findings are also presented. The E-views statistical tool has been used throughout
the analysis.
4.10 Model set up
To formalize the above observations, this section presents a vector autoregression (VAR)
analysis. The VAR model assumes that the Kenyan economy can be described by the following
structural form equation:

X t'  Yt
CPI t
rt
NEER t
M '
3
Where Yt is Real GDP, CPI is the price level, rt is the Repo rate, NEER is the nominal
exchange rate and M3 is money supply
The benchmark reduced-form VAR is stated as:
X t   0   1t  A ( L ) X t 1   t
Thus the relation between the reduced form disturbances  t and the structural disturbances  t
takes the following form:
47 0
 1

1
 21


  31  32
  41  42

 51  52
0
0
0
0
0
0
1
0
1
0
0

1


43
53
54
   tY  1
  CPI  
  t
 0

 
 M 3   
  t
 0
  REPO _ R  0
  t NEER  
  t
 0
0
1
0 0
0 0
0 1 0 0
0 0 1 0
0 0 0 1

vtY

  v CPI 
t






M3

  vt
 vtREPO _ RATE 

NEER 

  t
This recursive scheme entails that the ordering of the variables has important implications for
the identification of the shocks. This particular ordering has the following implications: (i)
Real GDP(Y) does not react contemporaneously to shocks from other variables in the system;
(ii) CPI does not react contemporaneously to shocks originating from all factors except real
GDP. (iii) Money stock responds contemporaneously to shocks originating from real GDP and
CPI while (iv) Repo rate is affected contemporaneously by all shocks in the system, except
those from the nominal effective exchange rate (v) nominal effective exchange rate is affected
contemporaneously by all shocks in the system.
Technically, this amounts to estimating the reduced form, then computing the Cholesky
factorization of the reduced form VAR covariance matrix. In other words, the relation between
the reduced-form errors and the structural disturbance is given by the above matrix.
4.2 PRELIMINARY ANALYSIS
This section outlines some preliminary tests to gauge the fitness of the model run. All the
variables were transformed to natural logarithms after seasonal adjustment apart from repo
rates. Macroeconomic time series variables mostly exhibit time variant moments. This can be
confirmed through stationarity test. In testing for stationarity, this study employed the
Augmented Dickey-Fuller (ADF) and Phillips Perron tests. ADF test was employed with
intercept and lag length selected based on the SIC information criterion to ensure that the
48 residuals are white noise. The decision criterion involves comparing the computed tau values
with the Mackinnon critical values for rejection of a hypothesis of a unit root.
Table 1. Test for stationarity results
Unit root test with trend and intercept
Variable
ADF
Level
PP
1st
Level
Conclusion
1st
GDP
-2.5650***
Difference
-5.0894
-2.3738***
Difference
-6.2196
I(1)
LN_CPI
-1.03173**
-3.7709
-0.6084**
-3.9612
I(1)
LN_NEER
-1.03171**
-3.7709
-0.6084**
-3.9612
I(1)
LNM3
-2.9103**
-7.2222
-2.9533
-7.2224
I(1)
REPO_RATE -2.6742**
-6.3865
-2.4196**
-8.9137
I(1)
***10percent, **5percent and *1percent significance levels. I(1) integrated of order one
Source: Author,(2014)
This test shows that all the variables are non- stationary in levels at 1percent, 5 percent and 10
percent significance level. This means that the individual time series have a stochastic trend
and do not revert to average or long run values after a shock strikes and the distributions has no
constant mean and variance.
4.1.2 Test for co-integration
Since variables have unit root at levels, we tested for long run relationship using the Johansen
and Juselius (1990) approach to establish the co-integrating vectors. Two test statistics are used
to test the number of co-integrating vectors, based on the characteristic roots. For both trace
and Eigen statistics, the null is at most r co-integrating vectors.
49 Table II: co-integration test
Hypothesized
Trace
0.05
No. of CE(s)
Eigen value
Statistic
Critical Value
None *
0.467381
105.2094
88.80380
At most 1 *
0.346820
66.78253
63.87610
At most 2
0.295412
40.80243
42.91525
At most 3
0.196487
19.44376
25.87211
At most 4
0.095153
6.099321
12.51798
Trace test indicates 2 co-integrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Co-integration Rank Test (Maximum Eigenvalue)
Hypothesized
Max-Eigen
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
None *
0.467381
38.42685
38.33101
At most 1
0.346820
25.98010
32.11832
At most 2
0.295412
21.35867
25.82321
At most 3
0.196487
13.34444
19.38704
At most 4
0.095153
6.099321
12.51798
Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Prob.**
0.0020
0.0279
0.0801
0.2554
0.4478
Prob.**
0.0487
0.2330
0.1744
0.3010
0.4478
Both the Eigen and Trace statistic rejects none co-integration hypothesis at 5percent
significance level for at 1 and 2 co integrating relationships respectively. This reveals that there
is enough statistical evidence for existence of a unique co-integrating vector for the set of
variables in the VAR model.
The optimal lag length was selected based on comparison of the following information criteria
which include Akaike information criterion (AIC) Schwarz information criterion (SC), Hannan
– Quinn information (HQ) criterion, Final prediction error (FPE) and Sequential modified LR
test statistic. Too many lags impact on degrees of freedom while few lags create the problem of
serial correlation. Majority of the criteria indicate that the optimal lag length should be 2.
50 Table III: VAR Lag Order
Selection Criteria
Lag
LogL
LR
FPE
AIC
0
115.6431
NA
1.62e-08 -3.750612
1
486.4991 666.2838
1.31e-13 -15.47455
2
516.3018 48.49250* 1.14e-13* -15.63735*
3
533.9352 25.70287
1.53e-13 -15.38763
4
557.1124 29.85547
1.79e-13 -15.32585
5
577.4850 22.78963 2.46e-13 -15.16898
* indicates lag order selected by the criterion
LR: sequential modified LR test statistic (each test at 5%
level)
FPE: Final prediction error
AIC: Akaike information
criterion
SC: Schwarz information
criterion
HQ: Hannan-Quinn information criterion
SC
-3.574549
-14.41817*
-13.70066
-12.57063
-11.62853
-10.59136
HQ
-3.681884
-15.06218*
-14.88134
-14.28799
-13.88256
-13.38206
51 Table IV: Reduced VAR Model Estimates
VECTOR AUTOREGRESSION ESTIMATES
LNGDP_SA
LNCPI_SA
LNGDP_SA(-1)
0.589740
0.020486
(0.13626)
(0.15949)
[ 4.32801]
[ 0.12845]
LNM3_SA
0.021580
(0.10288)
[ 0.20977]
REPO_RATE
79.29470
(28.0955)
[ 2.82233]
LNNEER_SA
-0.243230
(0.31433)
[-0.77382]
LNGDP_SA(-2)
0.092090
(0.13568)
[ 0.67874]
0.208808
(0.15881)
[ 1.31485]
0.034013
(0.10243)
[ 0.33205]
-59.93162
(27.9752)
[-2.14231]
0.037183
(0.31298)
[ 0.11880]
LNCPI_SA(-1)
-0.087132
(0.10151)
[-0.85838]
1.130840
(0.11881)
[ 9.51786]
-0.060375
(0.07664)
[-0.78781]
30.37508
(20.9298)
[ 1.45128]
0.149090
(0.23416)
[ 0.63671]
LNCPI_SA(-2)
0.168043
(0.10134)
[ 1.65819]
-0.291751
(0.11862)
[-2.45962]
0.091075
(0.07651)
[ 1.19035]
-51.35040
(20.8953)
[-2.45750]
-0.306202
(0.23377)
[-1.30983]
LNM3_SA(-1)
0.102655
(0.17000)
[ 0.60386]
-0.192374
(0.19898)
[-0.96682]
1.284277
(0.12835)
[ 10.0064]
-32.49276
(35.0515)
[-0.92700]
-0.859670
(0.39215)
[-2.19221]
LNM3_SA(-2)
-0.044330
(0.16967)
[-0.26127]
0.223310
(0.19859)
[ 1.12447]
-0.313341
(0.12810)
39.29742
(34.9837)
1.045571
(0.39139)
[-2.44612]
[ 1.12331]
[ 2.67143]
REPO_RATE(-1)
-0.000330
(0.00063)
[-0.52418]
-0.000105
(0.00074)
[-0.14239]
-8.37E-05
(0.00048)
[-0.17606]
0.667733
(0.12983)
[ 5.14305]
0.000892
(0.00145)
[ 0.61391]
REPO_RATE(-2)
0.000522
(0.00059)
[ 0.87761]
-0.001561
(0.00070)
[-2.24242]
-0.000771
(0.00045)
[-1.71710]
-0.080552
(0.12263)
[-0.65688]
-0.003607
(0.00137)
[-2.62879]
LNNEER_SA(-1)
0.014518
(0.05167)
[ 0.28096]
0.042705
(0.06048)
[ 0.70608]
-0.015767
(0.03901)
[-0.40416]
2.930079
(10.6544)
[ 0.27501]
1.013078
(0.11920)
[ 8.49903]
LNNEER_SA(-2)
-0.062643
(0.05176)
[-1.21027]
-0.014012
(0.06058)
[-0.23129]
0.012662
(0.03908)
[ 0.32402]
4.846918
(10.6721)
[ 0.45417]
-0.187440
(0.11940)
[-1.56988]
C
3.089220
(1.06721)
[ 2.89466]
0.995097
0.994136
-2.705269
(1.24914)
[-2.16571]
0.998339
0.998013
-0.395902
(0.80573)
[-0.49136]
0.999719
0.999664
-276.9739
(220.047)
[-1.25871]
0.673313
0.609257
1.558297
(2.46183)
[ 0.63298]
0.905546
0.887025
R-squared
Adj. R-squared
52 4.2 ESTIMATION OF IMPULSE RESPONSES
The effect of a monetary policy shock through the repo rate on real GDP appears to be
insignificant since the impact is not statistically distinguishable from zero, given that the
horizontal axis is broadly within the 95 percent confidence band in the 20 quarters time horizon
after the shock. On the other hand, a repo rate has a significant and persistent impact on prices
for 10 quarters before the effect decays afterwards. However the effect takes place after some
delay. An unexpected and temporary rise in the repo rate is followed by a nominal exchange
rate appreciation, with the impact experienced for almost six quarters. On the other hand, a
monetary shock has a significant and persistent impact on prices. An unexpected and temporary
rise in the Repo rate is followed by a decline in prices, with the effect picking 6 months after
the shock.
53 Response to Cholesky One S.D. Innovations ± 2 S.E.
Response of LNGDP_SA to REPO_RATE
Response of LNGDP_SA to LNM3_SA
.008
.008
.004
.004
.000
.000
-.004
-.004
-.008
-.008
2
4
6
8
10
12
14
16
18
2
20
4
Res ponse of LNCPI_SA to LNM3_SA
6
8
10
12
14
16
18
20
Res ponse of LNCPI_SA to REPO_RATE
.01
.01
.00
.00
-.01
-.01
-.02
-.02
2
4
6
8
10
12
14
16
18
2
20
Response of LNNEER_SA to LNM3_SA
4
6
8
10
12
14
16
18
20
Response of LNNEER_SA to REPO_RATE
.03
.03
.02
.02
.01
.01
.00
.00
-.01
-.01
-.02
-.02
-.03
-.03
2
4
6
8
10
12
14
16
18
20
2
4
6
8
10
12
14
16
18
20
The above empirical findings suggest that Kenya’s nominal exchange rate is susceptible to
open market operations, with appreciation following an increase in the repo rates, explained by
capital inflow associated with interest rate differentials vis-à-vis other countries. On the other
hand, strengthening of the currency following monetary tightening in turn makes imports
cheaper, thereby decreasing the overall price level and the rate of inflation. Open market
operations; however, seems to have little impact on the real output probably due to structural
54 weaknesses in the financial sector, which are likely to hamper the transmission mechanism of
monetary policy, Cheng (2006). Main structural weaknesses, as identified by the Fund’s
Financial Sector Stability Assessment Report, include weak legal framework, poor governance,
and insufficient infrastructure, which have contributed to high interest rate spreads, inadequate
financial intermediation and heightened risks. We however note that a monetary policy shock
has significant and persistent impact on prices.
Consistent with the impulse response analysis, a monetary policy shock has significant impact
on prices while output and the real exchange rate and GDP are relatively sluggish vis-à-vis the
monetary policy shock. Given that monetary stance is perceived to have little impact on
agriculture in Kenya- which is largely driven by exogenous factors beyond the control of the
CBK, such as weather-the large share of agriculture on Kenya’s GDP appears to provide for an
apparent reason for the insignificant relationship between total output and monetary policy.
4.2 INTERPRETATIONS OF THE ECONOMETRIC RESULTS
The above empirical findings suggest that Kenya’s nominal exchange rate is highly susceptible
to monetary policy, with appreciation following an increase in the repo rate, probably reflecting
capital mobility associated with interest rate differentials vis-à-vis other countries. The
strengthening of the currency following monetary tightening in turn makes imports cheaper,
thereby decreasing the overall price level and the rate of inflation. This is also explained by
market behavior as dealers unwind long dollar positions in favor of the strong demand for the
local currency. Monetary policy, however, seems to have little impact on the real output. This
is not a surprising result given the slew of structural weaknesses in the financial sector, which
are likely to hamper the transmission mechanism of monetary policy.
55 CHAPTER 5
5
RESULTS, RECOMMENDATIONS AND CONCLUSIONS
Monetary policy refers to the use of instruments under the control of the central bank to
regulate the availability, cost and use of money and credit. Beginning with Sims (1980), small
structural vector autoregression models have become an increasingly popular means of
modeling monetary policy. This paper studies the transmission mechanism of monetary policy
based on a vectorautoregression framework for Kenya using quarterly time series data for
1997Q1 – 2014Q4. The findings suggest that an exogenous, unexpected, and temporary rise in
the CBK’s REPO rate tends to be followed by nominal exchange rate appreciation and falling
prices, with impact on output being insignificant. This is consistent with intuition and the
findings of Cheng (2006) on the Kenyan economy.
A plausible explanation for the sluggish response of output to a monetary policy shock is that
the Kenyan financial system is plagued with structural weaknesses, thereby hampering the
monetary transmission to the real sector. Further, the larger component of the real sector
(agriculture) is largely driven by exogenous factors beyond the control of the CBK. Looking
forward the Kenyan authorities should continue to undertake structural reforms aimed at
addressing the weaknesses in the financial sector. This includes improving liquidity redistribution, strengthening the regulatory framework, as well as and incorporating Islamic
banks to the Kenyan financial system with a view to improving the monetary transmission
mechanism to the real sector.
It is also necessary that a number of caveats need to be taken in account while interpreting the
results. First, the sample period is relatively short. Therefore, the findings may only pertain to
56 idiosyncratic economic developments during the sample period, while not necessarily serving
as a best guide as to how the Kenyan economy would work in the future. Second, poor data
quality, particularly the output data, is a concern. Specifically, given the large size of the
informal sector, national accounts statistics may not capture important activities that are
influenced by the monetary policy stance.
Lastly, fiscal policy deals with the taxation and expenditure decisions of the government. These
include, tax policy, expenditure policy, investment or disinvestment strategies and debt or
surplus management. There is therefore need for coordination between fiscal and monetary
policy for monetary policy to be fully effective. Lack of coordination will result in duplication
of efforts and negative externalities (negative spill-overs).
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Table 1. Summary Statistics of the Variables
obs CPI GDPN INFL LNCPI LNCPI_SA LNGDP LNGDP_SA LNINFL LNNEER LNNEER_SA LNREPORATE 1997Q4 40.95 218369.4 8.38 3.71235 3.713056 12.29394 12.34373 2.125848 4.14393 4.147442 3.277145 63.05
1998Q1 42.83 236284.5 7.63 3.75724 3.771243 12.37279 12.35219 2.032088 4.09651 4.112055 3.198673 60.13
1998Q2 42.86 241941.8 7.39 3.75794 3.757995 12.39645 12.35605 2.000128 4.10297 4.091906 3.104587 60.52
1998Q3 43.4 231504.7 6.51 3.77046 3.756108 12.35236 12.36353 1.873339 4.09451 4.087195 2.397895 60.01
1998Q4 42.46 225696.6 4.06 3.74856 3.748738 12.32695 12.37624 1.401183 4.12423 4.12711 2.110213 61.82
1999Q1 43.4 244212.9 4.01 3.77046 3.784543 12.4058 12.38652 1.388791 4.15904 4.173992 2.079442 64.01
1999Q2 44.94 250060 3.66 3.80533 3.805547 12.42946 12.38895 1.297463 4.29865 4.2884 2.791165 73.6
1999Q3 46.32 236378.7 4.17 3.83557 3.821336 12.37319 12.38324 1.427916 4.32651 4.319518 2.881443 75.68
1999Q4 46.8 230448.3 5.78 3.84588 3.845538 12.34778 12.39595 1.754404 4.30325 4.304669 2.014903 73.94
2000Q1 46.73 249354.4 7.36 3.84439 3.858752 12.42663 12.40969 1.99606 4.30986 4.32392 2.302585 74.43
2000Q2 49 255324.6 8.4 3.89182 3.891735 12.45029 12.41104 2.128232 4.35092 4.343616 2.341806 77.55
2000Q3 51.63 243956 9.61 3.9441 3.930477 12.40474 12.41154 2.262804 4.35927 4.352121 2.558002 78.2
2000Q4 52.21 230417 9.97 3.95527 3.95465 12.34765 12.39462 2.299581 4.36602 4.366006 2.679651 78.73
2001Q1 51.66 244785 10.66 3.94468 3.958744 12.40814 12.39515 2.366498 4.3535 4.365876 2.509599 77.75
2001Q2 52.35 257176 10.06 3.95795 3.957546 12.45752 12.41843 2.308567 4.36463 4.360655 2.408745 78.62
2001Q3 53.58 248990 8.06 3.98118 3.968674 12.42517 12.42901 2.086914 4.36882 4.361833 2.386926 78.95
2001Q4 53.42 244856 5.73 3.97819 3.977805 12.40843 12.45566 1.745716 4.36552 4.363449 2.319442 78.69
2002Q1 52.29 260682 3.49 3.95681 3.969728 12.47106 12.4596 1.249902 4.35748 4.368981 2.09679 78.06
2002Q2 53.3 265474 2.28 3.97594 3.974475 12.48927 12.4515 0.824175 4.36514 4.363556 1.987874 78.66
2002Q3 54.6 259267 1.81 4.00003 3.989534 12.46561 12.46572 0.593327 4.36704 4.359901 2.111425 78.81
2002Q4 54.97 245412 1.97 4.00679 4.007327 12.41069 12.46016 0.678034 4.37613 4.37306 1.754404 79.53
2003Q1 56.45 254233 3.63 4.03336 4.044271 12.44601 12.43513 1.289233 4.33834 4.349645 ‐0.105361 76.58
2003Q2 60.46 266673 6.54 4.10198 4.099337 12.49378 12.45395 1.877937 4.30027 4.29916 ‐0.71335 73.72
2003Q3 59.53 257854 8.34 4.08648 4.078356 12.46015 12.46121 2.121063 4.35543 4.348512 ‐0.105361 77.9
2003Q4 59.8 246466 9.81 4.09101 4.092714 12.41498 12.46694 2.283402 4.328006 0.392042 76.02
2004Q1 61.59 270865 10.06 4.1205 4.128708 12.50938 12.49511 2.308567 4.34718 4.357997 0.336472 77.26
2004Q2 64.11 280468 8.19 4.1606 4.15694 12.54421 12.50305 2.102914 4.37286 4.372311 0.924259 79.27
2004Q3 68.09 275763 9.59 4.22083 4.215349 12.5273 12.5324 2.260721 4.39099 4.382498 1.99606 80.72
2004Q4 70.32 258815 11.79 4.25306 4.255897 12.46387 12.51659 2.467252 4.37915 4.378669 1.985131 79.77
2005Q1 70.41 279578 13.07 4.25434 4.259343 12.54104 12.52212 2.57032 4.31482 4.323455 1.997418 74.8
2005Q2 73.22 295389 15.1 4.29347 4.289874 12.59605 12.55384 2.714695 4.33964 4.34024 2.055405 76.68
2005Q3 73.23 281288 13.24 4.29361 4.290489 12.54713 12.55992 2.583243 4.30542 4.296175 2.054124 74.1
4.29197 4.293372 1.961502 73.11
2.152924 4.28055 4.286424 1.811562 72.28
4.29606 4.29802 1.826161 73.41
2.2895 4.331 2005Q4 73.33 277822 9.87 4.29497 4.297761 12.53474 12.58511 2006Q1 76.66 303028 8.61 4.33938 4.342148 12.62158 12.59593 2006Q2 76.68 312996 6.33 4.33964 4.33636 12.65395 12.61523 2006Q3 76.89 298188 5.7 4.34238 4.341002 12.60548 12.62382 1.740466 4.28868 4.279433 1.848455 72.87
2006Q4 78.5 295140 6.39 4.3631 4.365864 12.59521 12.64239 1.854734 4.2432 4.246029 1.912501 69.63
2007Q1 79.17 327868 4.99 4.3716 4.372496 12.70037 12.66812 1.607436 4.2383 4.241614 1.957274 69.29
2007Q2 78.69 328265 4.46 4.36552 4.362751 12.70158 12.66962 1.495149 4.19825 4.200602 2.129421 66.57
2007Q3 81.07 319085 4.57 4.39531 4.395145 12.67321 12.6931 1.519513 4.20499 4.196972 2.004179 67.02
2007Q4 82.99 319476 4.27 4.41872 4.421115 12.67444 12.71837 1.451614 4.14789 4.151401 1.873339 63.3
1.8453 62 NEER
2008Q1 87.58 348569 6.13 4.47255 4.472767 12.76159 12.72599 1.813195 4.17316 4.174646 1.957274 64.92
2008Q2 92.49 349744 9.86 4.5271 4.524189 12.76496 12.74005 2.288486 4.15544 4.15797 1.783391 63.78
2008Q3 95.72 323262 13.02 4.56143 4.561849 12.68622 12.70332 2.566487 4.26844 4.260211 1.791759 71.41
2008Q4 98.51 327191 16.27 4.59016 4.592839 12.6983 12.73998 2.789323 4.35722 4.361921 1.432701 78.04
2009Q1 99.99 357816 17.07 4.60507 4.604985 12.78777 12.75106 2.837323 4.38527 4.387408 1.432701 80.26
2009Q2 101.91 349372 15.11 4.62409 4.62057 12.76389 12.74703 2.715357 4.35478 4.355583 1.011601 77.85
2009Q3 102.9 341264 12.41 4.63376 4.634835 12.74041 12.7527 2.518503 4.32546 4.317618 1.386294 75.6
2009Q4 104.07 330274 9.24 4.64506 4.647546 12.70768 12.74375 2.223542 4.32321 4.327534 0.8671 75.43
2010Q1 105.01 359669 7.03 4.65406 4.654598 12.79294 12.76108 1.950187 4.34316 4.34781 0.667829 76.95
2010Q2 105.65 361624 5.43 4.66013 4.655385 12.79836 12.78709 1.691939 4.3947 4.392994 0.609766 81.02
2010Q3 106.32 357141 4.4 4.66645 4.668149 12.78589 12.79443 1.481605 4.39334 4.385189 0.357674 80.91
2010Q4 108.07 347698 3.96 4.68278 4.685582 12.75909 12.7865 1.376244 4.38913 4.393031 0.506818 80.57
2011Q1 112.42 381732 4.49 4.72224 4.72291 12.85247 12.82767 1.501853 4.43331 4.442119 1.7492 84.21
2011Q2 119.56 374769 6.88 4.78382 4.777804 12.83407 12.82819 1.928619 4.4892 4.484183 2.876386 89.05
2011Q3 123.88 379857.1 10.18 4.81931 4.821923 12.84755 12.85378 2.320425 4.56809 4.559051 2.476538 96.36
2011Q4 128.81 384945.2 14.02 4.85834 4.861464 12.86086 12.87642 2.640485 4.46199 4.466187 2.572612 86.66
2012Q1 131.36 390033.3 16.45 4.87794 4.878381 12.87399 12.85982 2.800325 4.41764 4.428665 2.863343 82.9
2012Q2 133.63 395121.4 15.97 4.89508 4.888462 12.88695 12.88276 2.770712 4.44018 4.434552 2.274186 84.79
2012Q3 131.78 400209.5 13.29 4.88113 4.884171 12.89974 12.90492 2.587012 4.43805 4.427135 1.859418 84.61
2012Q4 133.35 405297.6 9.38 4.89298 4.896441 12.91238 12.9197 2.23858 4.45423 4.45908 2.247072 85.99
2013Q1 136.72 410385.7 6.33 4.91794 4.918092 12.92485 12.91764 1.8453 4.45225 4.464949 2.125848 85.82
2013Q2 139.46 415473.8 4.56 4.93778 4.930734 12.93717 12.93375 1.517323 4.4484 4.442633 1.94591 85.49
2013Q3 140.99 420561.9 4.75 4.94869 4.952187 12.94935 12.95384 1.558145 4.47061 4.458372 2.474014 87.41
2013Q4 143.25 5.72 4.96459 4.968104 12.96137 12.96508 1.743969 4.45795 4.462884 2.107786 86.31
6.39 4.98354 4.983545 12.97326 12.9701 1.854734 4.46003 4.473496 NA 86.49
425650 2014Q1 145.99 430738.1 63