Flexible Inflation Targeting and Relevance of Monetary ...€¦ · Email: [email protected] Abstract Under monetary aggregate targeting regime, inflation is considered as

Flexible Inflation Targeting and Relevance of Monetary Aggregates for Inflation

in Pakistan

By Fayyaz Hussain,

* Economist, Monetary Policy Department, State Bank of Pakistan, Pakistan

Email: [email protected]

Abstract

Under monetary aggregate targeting regime, inflation is considered as a monetary

phenomenon. However, in emerging economies various inflation shocks such as financial

innovations and correction in administered prices has made this relationship questionable. As

a result, many emerging economies have abandoned monetary aggregate targeting. In line

with the global trend, Pakistan has abandoned monetary aggregate targeting and is planning to

adopt flexible inflation targeting by 2020. This study attempts to assess the relevance of

monetary aggregates for monetary policy decision making under the new framework. This

study uses event study as well as Structural Vector Auto regression (SVAR) method to assess

the relationship between money and inflation on aggregate as well as disaggregated basis.

This study found that monetary aggregate and its components are important determinant of

inflation. Within its components, net domestic assets expansion and budgetary borrowings

from the banking system are the most inflationary components of broad money while credit to

private sector and net foreign assets are least inflationary. The study concludes that in the new

monetary framework, trend in monetary aggregates and its components are still informative

about the future plausibility of price stability. Disaggregated analysis indicates that narrowing

of the twin deficits would help contain inflation in the economy.

Keywords: Monetary aggregates, inflation, disaggregated, Monetary Policy

Framework.

JEL classification: E31, E41, E51, E52

mailto:[email protected]

Flexible Inflation Targeting and Relevance of Monetary Aggregates for Inflation in Pakistan

1

1. Introduction.

Monetary aggregates have long been understood to play a central role in

monetary policy by predicting the future movements in prices and income. This

relationship connecting money with income and prices was also supported by a rich

literature.1 However, financial innovations and deregulation altered this familiar

relationship.2 As a result, role of monetary aggregates in monetary policy analysis

has reduced significantly across the globe. This has led the main stream monetary

policy analysis to focus on adjustments in short term interest rate rather than any

monetary aggregates.

Pakistan like other developing countries is no exception to this paradigm shift in

monetary policy analysis. As Pakistan has also gone through financial reforms and

consequent financial innovations, this raised doubts about stability of demand for

money in Pakistan3. As a result of this unpredictable relationship between money

growth and inflation and lose control over reserve money because of fiscal dominance,

State Bank of Pakistan has switched from monetary aggregates to interest rate as the

operating target in 2009. In this backdrop, the natural question is what role money

could play in assessing the achievement of policy objectives in this new policy

environment.

1 For instance see the literature survey by Friedman (1990). 2 For example see earlier empirical work for United States by Bernanke and Blinder (1988), Friedman

and Kuttner (1992) and recent empirical work for euro area by Beyer, Fischer, and von Landesberger,

2007; Fischer, Lenza, Pill, and Reichlin, 2007; Fischer and Pill, 2010. 3 For instance, Moinuddin (2009) and Omar and Saqib (2009) documented unstable demand for money

in Pakistan.


2

In Pakistan, money supply is still considered an important information variable to

assess inflation. Therefore, SBP closely monitors trends in monetary aggregates to

gauge the plausibility of achieving the objective of price stability. This study is an

attempt to reexamine the relationship between money growth and inflation in Pakistan.

While the previous studies explored this relationship on aggregated level, 4 this study

benefits from a more detailed disaggregated data on monetary aggregates. Along with

evaluating the dynamic impact of the overall monetary expansion on inflation, this

study also explores the impact of disaggregated monetary aggregates on inflation in

Pakistan.

The study finds that relationship between real money balances growth and inflation is

strong at aggregated as well as disaggregated level and hence could be useful in

predicting the future inflation. Within monetary aggregate, expansion in net domestic

assets are more inflationary while expansion in net foreign assets has no significant

impact on inflation. Specifically, budgetary borrowings from the banking system that

constitutes a large part of domestic assets seem to be the most inflationary

components of money balances. It implies that efforts to curtail inflationary pressures

must be accompanied with the discipline on the fiscal side.

The rest of the study is organized as follow. The next section is about potential role of

monetary aggregate in new framework. The following section is the descriptive data

analysis of money and inflation. Fourth section discusses a small event study followed

4 For instance see Abbas and Hussain (2006), Qayyum (2006) and Husain & Rashid, (2006) etc


3

by a section elaborating the VAR methodology. The sixth section discusses results

while the final section concludes the study.

2. Potential Role for Money under Flexible Inflation Targeting

Under Flexible Inflation Targeting (FIT), the overriding objective of Monetary

Authorities (MA) across the world is to achieve price stability. At the same time, MA

also minimizes the undesirable fluctuations in other key macroeconomic variables

such as economic growth. To achieve this objective, central banks choose appropriate

intermediate and operational targets. Typically, the intermediate target is the variable

which helps in predicting the path of ultimate targets while the operational target is

the variable that the central bank can control on daily basis.

While there is a range of intermediate targets such as broad money, inflation forecast,

nominal exchange rate and nominal gross domestic product to choose from, there is

relatively limited choice between interest rate and reserve money as the operational

targets. The literature (Poole 1970) suggests that the decision to choose between

money and interest rate as the operational target mainly depends on the relative

frequency of money demand shocks and aggregate demand shocks. In case of more

prevalence of money demand shocks, interest rate rule performs better while in case

of more frequent aggregate demand shocks money targeting is suitable.

In Pakistan’s case, money demand shocks are more frequent. Specifically, abrupt

changes in the government borrowing from State Bank of Pakistan (SBP) and erratic


4

behavior of foreign inflows are beyond SBP’s control and difficult to predict. In the

presence of these shocks, hitting the reserve money target is possible only at the costs

of very large changes in the interest rate. Thus natural choice for Pakistan is to choose

interest rate as the operation target. Pakistan switched to this target in 2009. In

strategic plan for 2016-2020, State Bank of Pakistan envisioned to adopt flexible

inflation targeting by 2020.

Along with shifting to flexible inflation targeting, State Bank of Pakistan has started

making its decision on the basis of policy input provided by New-Keynesian Models

such as forecasting and policy analysis system (FPAS). These models widely used for

policy advice do not make any reference to monetary aggregates (Taylor, 1999).

Although monetary aggregates does not play central role in the new regime, it is not

desirable for SBP to ignore monetary aggregates entirely. This is because they still

contain useful information for assessing the future path of ultimate target of price

stability. They may play the same role as played by the other key variables such as

exchange rate, industrial production index, inflation expectations survey, fiscal

accounts and external accounts in assessing the future path of ultimate targets. For

instance, monetary aggregates are still useful for the following reasons.

First, data on monetary aggregates is available in the timely manner and is less subject

to revisions. As Friedman (1990s) suggests the changes in money balances could

convey information about fluctuations in Gross Domestic Production (GDP). This


5

argument fits well for Pakistan where GDP data is available on annual basis. Thus

weekly monetary trends could be used as an indicator of economic activity in Pakistan.

Second, analysis of monetary aggregates may be more useful for monetary and fiscal

policies coordination. Specifically, Pakistan is suffering from fiscal dominance where

relying on interest rates alone may not be sufficient to control and assess inflation.

This is because relatively less interest rate elastic government borrowings from the

banking system dilutes the effectiveness of monetary policy. Thus composition of

monetary aggregates conveys information about the plausibility of meeting the

objective of price stability.

Third, monetary aggregates are considered as the more reliable indictors of tightness

of monetary policy than interest rates. For instance, in the 1980s both the short term

interest rates and monetary growth fell sharply in United States. Looking solely at

interest rates suggested that this period was one of the extreme monetary policy ease

while sharp fall in monetary growth indicated tight monetary policy. The mid-1980s

economic downturn, however, showed that monetary policy was in fact tight and that

interpretation of monetary policy based on monetary aggregates is more reliable than

that of short-term interest rates (McCallum and Edward (2010)).


6

FY8

2

FY8

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FY8

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FY8

8

FY9

0

FY9

2

FY9

4

FY9

6

FY9

8

FY0

0

FY0

2

FY0

4

FY0

6

FY0

8

FY1

0

FY1

2

FY1

4

FY1

6

3. Descriptive Analysis 3.1: Simple Correlation

For descriptive analysis, we have used last 36 years annual data spanning from 1980

to 2016. The data suggests that average broad money growth during this period was

14.8 percent while average inflation during the same period was 8.5 percent. Unlike

considerable difference in means, the volatility of both the series was almost same as

is depicted by standard deviation of around 4 during the period under review.

Figure 1: Broad Money Expansion and Inflation Mo netary Expansion Inflat io n

25

20

15

10

5

0

Figure1 shows positive correlation between monetary expansion and inflation.

Figure 2 shows the correlation between inflation and leads and lags of monetary

expansion. It may be observed from the figure that contemporaneous correlation

between inflation and money growth is low. Importantly, lags of money growth has

strong correlation with inflation that indicates that money growth can be used as a

leading indicators for future price movements. .


7

Figure 2: Dynamic Correlation between Monetary Growth and Inflation

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

-42 -39 -36 -33 -30 -27 -24 -21 -18 -15 -12 -9 -6 -3 0 3 6 9 12

Figure 3: Dynamic Correlation between Inflation and Components of Money Growth

0.50

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.60

0.50

0.40

0.30

0.20

0.10

0.00

NDA Growth

-42 -39 -36 -33 -30 -27 -24 -21 -18 -15 -12 -9 -6 -3 0 3 6 9 12

Govt Borrowing Growth

-42 -39 -36 -33 -30 -27 -24 -21 -18 -15 -12 -9 -6 -3 0 3 6 9 12

0.1

0.05

0

-0.05

-0.1

-0.15

-0.2

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

-0.05

-0.10

-0.15

-0.20

NFA Growth

-42 -39 -36 -33 -30 -27 -24 -21 -18 -15 -12 -9 -6 -3 0 3 6 9 12

Private Sector Credit Growth

-42 -39 -36 -33 -30 -27 -24 -21 -18 -15 -12 -9 -6 -3 0 3 6 9 12

Within the components of monetary aggregates, expansion in net domestic assets and

government borrowings from the banking system has strong contemporaneous

correlation with inflation while credit to private sector has very weak correlation with

inflation. This probably reflects the fact that government borrowings from the banking


8

system are usually used to finance current expenditures that adds more to aggregate

demand than aggregate supply and leads to inflationary pressures in the economy.

However, credit to private sector not only adds to aggregate demand but also enhance

productive capacity of the economy. As a result, economy can grow at a higher rate

without generating inflationary pressures. Interestingly, there is a negative correlation

between expansion in net foreign assets and inflation. This probably reflects the fact

that build up in net foreign assets is associated with better external inflows that leads

to exchange rate stability. This stability in exchange rate cascades to consumer prices

through stable prices of the imported items. Further, exchange rate stability also leads

to stability in inflation expectations of the households and businesses that help contain

inflation. This suggests that along with looking at monetary expansion at aggregated

level, the disaggregated monetary aggregates is also important for plausibility of price

stability.

The above analysis suggests that a) correlation between money growth and inflation

with lag is high than contemporaneous correlation between the two and b) growth in

some of the components of broad money (budgetary borrowing) has high correlation

with inflation than that of other components.

3.2: Granger Causality

So far we were looking at the simple correlation which tells nothing about causation.

In order to check the causation, we applied Granger causality test on the annual data

from 1980-2016.


9

Granger causality tests shows that money growth does Granger cause inflation but

inflation does not Granger cause money growth. Regarding components of broad

money, growth in net domestic assets and growth in government borrowings from the

banking system does Granger cause inflation but inflation does not granger cause

these components.(see Table 3). Further, neither NFA growth nor inflation causes

each other. Likewise, there is no causation in either direction between private sector

credit growth and inflation. These results are consistent with our simple correlation

analysis.

Table 1: Pairwise Granger Causality Tests

Null Hypothesis: Obs F-Statistic Prob.

Money Growth does not Granger Cause Inflation

34

6.67

0.00

Inflation does not Granger Cause Money Growth 0.52 0.60

Net Domestic Assets Growth does not Granger Cause Inflation

34

3.33

0.05

Inflation does not Granger Cause Net Domestic Assets Growth 1.94 0.16

Net Foreign Assets Growth does not Granger Cause Inflation

34

0.25

0.78

Inflation does not Granger Cause Net Foreign Assets Growth 0.83 0.45

Government Borrowing Growth does not Granger Cause Inflation

34

2.73

0.08

Inflation does not Granger Cause Government Borrowing Growth 0.72 0.49

Private Sector Credit does not Granger Cause Inflation

34

0.48

0.63

Inflation does not Granger Cause Private Sector Credit 0.60 0.56


10

4. Methodology 4.1-Event Study

In this case we divided the money growth and inflation into high growth episodes and

low growth episodes. Since average inflation for last 66 years (1951-2016) is 7.5

percent, we considered inflation above this rate as high inflation and below this rate as

low inflation. Likewise, average money growth during last 66 years is 13.6 percent, so

money growth above this rate is considered as high and below this rate as low money

growth.

Based on this categorization, we compare the episodes of both episodes of high and

low growth money with the inflation in the subsequent year. Specifically, we divided

the events into four distinct categories. These categories are a) high growth in broad

money followed by high inflation in the next period, b) high growth in broad money

not followed by high inflation in the subsequent period, c) low growth in broad

money is not followed by lower inflation and d) lower growth in broad money is

followed by low inflation in the next period.

4.2-Structural VAR

Following Irving Fisher, we use following quantity equation of exchange to study

monetary dynamic of inflation.

M tVt PtYt


11

* * *

Where M, V, P and Y are the quantity of money, the income velocity, the price level

and real income respectively. This equation can be written into price equation as

follow:

Pt M tVt / Yt

Taking log of the equation we get.

log( Pt ) log( M t ) LOG(Vt ) log(Yt )

To get the equation for inflation, we difference the equation.

1 dP

1 dM 1 dV

1 dY

P dt M dt V dt Y dt

Or

t Mt Yt Vt

Where π is YoY inflation, M *

is YoY growth in money, Y * is YoY growth in income

and V *

is YoY growth in income velocity of money. We assume constant income

velocity. i.e V *

equal zero.

-

To estimate this equation, the author preferred VAR over simple Ordinary Least

Square on the following grounds. First, our variables are simultaneously related which

implies biased OLS estimates. Second, VAR analysis is superior to a single equation

approach for allowing feedback among the variables and capturing the long run

dynamics of variables.


12

We relied on time series properties of the data to select the appropriate VAR to

estimate this equation. It may be pointed out there are three possible VAR

specifications to estimate this equation based on unit root test and co-integration test.

First, if all the variables are integrated of order zero i.e I(0), then long run relationship

among the variables is out of question and the appropriate technique is standard VAR

in level.

Second, if all the variables are integrated of order one i.e I(1) and there is no co

integration among the variables, the standard case is VAR in first difference.

Third, if all the variables are integrated of order one i.e I(1), and long run relationship

among variables could not be rejected then Error Correction term has to be included

in the VAR. This is called Vector Error Correction Model (VECM) which can be seen

as restricted VAR.

In our case, all the variables are level stationary, so we apply Standard VAR in level.

For this technique we consider a simple covariance stationary trivariate dynamic

simultaneous equations model:

Where


13

1

yt 0 2 0 0 2

t i.i.d 0, 0 2 0

0 0

0 2

mt 3

This model is called a structural VAR (SVAR), since it is assumed to be derived by

some underlying economic theory. The exogenous error terms yt ,

t and mt

are

independent and interpreted as structural innovations. Specifically, yt ,

t

and

mt are unexpected shocks to real output, inflation and real money supply that are

uncorrelated with one another.

In the matrix form, the model becomes,

+

This can be written as:

X t 0 1 X t 1 t

Where X t is a vector given by:

Or

p

X t A0 A1 X t 1 t i1


14

Where p is the optimal lag length necessary to turn error term t

white noise.

It may be pointed out that structural shocks are unobservable. However, these shocks

can be identified by using information from running reduced form VARs and

imposing some identifying restrictions based on economic theory. Following

Christiano et al (2001), we identify the monetary shock mt

by imposing the

following contemporaneous restrictions:

A)- Monetary shocks do not affect output within the same month i.e b13 = 0

B)-Monetary Shocks do not affect inflation within the same month i.e b23 = 0

For the disaggregated analysis, we ran six different VARs. One for aggregate money

and five each for different components (Net Domestic Assets, Net Foreign Assets,

government borrowing from the banking system and credit to private sector) of broad

money.

In addition to running a parsimonious tri-variate VAR, we tried to address the

possible problem of omitted variable bias by including other determinants of inflation.

Specifically, the simple VAR was extended to include global oil prices and exchange

rate.


15

* *

In the new specification, X t is a vector given by:

Where POLt

is the YoY growth in global oil prices, and ERt

is the depreciation

(+)/appreciation (-) of exchange rate.

5 Data and Results

5.1-Event Study

The results of the event study show that in the last 36 years5, in 23 years above

average money growth was followed by above average inflation rate in the next year

and below average money growth was followed by below average inflation rate in the

next year (Table 2). This indicates that around two thirds of the time money growth

was able to predict inflation in the next year.

In the rest of the years, movement in broad money was not able to predict the next

year inflation. During these years, however, changing composition of the broad

money provided useful information to predict future inflation.

There were only 6 occasions when above average money expansion was followed by

below average inflation. During this period, expansion in Net Foreign Assets (NFA)

5 Disaggregated data of monetary assets is available from 1978 onward only.


16

Inflation > 7.5%

15a 7c

22

NDA growth

Contribution in M2 growth

Net Domestic Assets

Budgetary Borrowing

18

91

42

15

127

65

had considerable contribution behind money expansion. Specifically, 23 percent of

expansion in money was contributed by NFA during those 6 years. NFA expansion

was accompanied with appreciation of exchange rate which had dampening effect on

inflation rate. Further budgetary borrowing which is considered as most inflationary

component of broad money contributed only 39 percent in the overall monetary

expansion in those years.

Table 2: Relationship between Money growth in inflation (1981-2016)

M2 (-1) growth > 13.6 M2 (-1) growth <13.6

Years

Years

Inflation < 7.5%

NDA growth

Contribution in M2 growth

Net Domestic Assets

Budgetary Borrowing

6b 8d

14

11.0 10.9

77 102

39 29

Tot-number of years 21 15 36

Source: Authors Calculations, a: High money growth high inflation, b: High money growth low inflation, c: Low money

growth high inflation, d: low money growth low inflation

Likewise, for the 7 years below average monetary was followed by above average

inflation in the following year. During these years, budgetary borrowing alone

contributed on average 65 percent in overall monetary expansion while NFA showed

contraction.


17

In both the above cases, where above/below average money growth is not followed by

above/below average inflation rate in the following year, compositional changes in

monetary expansion are helpful in explaining next year inflation. Specifically, growth

in broad money driven by expansion in net domestic assets is more inflationary than

growth in broad money that is driven by expansion in net foreign assets.

5.2-Structural VAR

We used annual data on growth rates of Real Gross Domestic Products, real money

supply, real government borrowing from the banking system, real Net Domestic

Assets, real Net Foreign Assets, real credit to private sector and Consumer prices

index (CPI). The data covers period from 1980-2016.

Table 3 reports the estimates of the unit roots tests for the stationarity of the variables.

All the variables are stationary at level i.e they are Integrated of order zero I(0). Since

the variables do not contain unit roots, the presence of co integration among the

variables could not be determined. This suggests a standard VAR in level. In order to

choose the optimal lag length, we used Akaike information criterion (AIC), Schwarz

information criterion (SC) and Final prediction error (FPE). These criteria suggest

optimal lag length of two to render the residuals white noise.


18

5.2.1. Analysis of Impulse Responses Figure 4 captures the dynamic effect of growth in real money balances and its

components on inflation over a horizon of ten years. The components of real money

balances include NDA, NFA, budgetary borrowing from the banking system and

credit to private sector. First we analyze the impact of unanticipated real money

balances shock on inflation and then that of components of real money balances.

The Impulse Response Function (IRF) of inflation shows that unanticipated real

money balances shocks has positive impact on inflation. This impact reaches at its

peak after two year when as a result of one standard deviation unanticipated shock to

growth in real money balances, inflation rises by 145 basis points. After this period

the positive impact of real money balances shocks on inflation gradually dies down.

This suggests that unanticipated real money balances shocks would result in higher

inflation rate in Pakistan. Ninety five percent confidence interval shows that impact of

unanticipated shock to real money balances on inflation remains statistically

significant in the first four to five year. After this period the impulse becomes

statistically insignificant and gradually dies out.

Analysis of the IRF of inflation to unanticipated shocks to components of real money

balances yields some interesting insights. For instance, unanticipated shock to real

NDA growth has much pronounced positive impact on inflation while unanticipated

shock to real NFA growth has negative impact on inflation (figure 4). This

contrasting impact of two components of real money balances on inflation may


19

apparently be attributed to exchange rate dynamics. As positive shock to NFA means

higher foreign inflows that potentially strengthen the rupee dollar parity. This

appreciation of exchange rate passes through to lower inflation. On the other hand,

positive shock to NDA reflects higher rupee liquidity in the system that could weaken

the exchange rate. As a result, depreciating local currency has positive impact on

inflation.

Specifically, one standard deviation unanticipated shocks to real net domestic assets

increases the inflation by around 100 basis points in the first two years and then the

impulse gradually dies down. Ninety five percent confidence interval shows that this

impact is statistically significant in the first three and a half years.

Impact of unanticipated shock to real net foreign assets on inflation is negligible.

Ninety five percent confidence interval shows that this impact is not statistically

significant.

Difference is also observed between the impact of net budgetary borrowing and credit

to private sector on inflation. In line with our expectations, one standard deviation

unanticipated shock to real net budgetary borrowing growth has relatively higher

impact on inflation than the impact of one standard deviation real private sector credit

growth shock. This difference may be explained by the output dynamics.

It may be pointed out that a large part of government expenditures in Pakistan are

current in nature. Thus unanticipated shock to government borrowing from the


20

banking system may lead to aggregate demand pressure. However being current in

nature, these expenditure are less likely to boost the productive capacity of the

economy. The resultant output gap, owing to unmatched increase in productive

capacity, possibly leads to inflationary pressures in the economy.

On the other hand positive shock to private sector credit may boost investment

activities in the economy as well. Thus besides increasing aggregate demand, this

shock also increase productive capacity of the economy. This could be the probable

reason of relatively benign impact of unanticipated private sector credit shock on

inflation than that of the impact of unanticipated budgetary borrowing shock.

In particular, one standard unanticipated shock to government borrowings from the

banking system increases the inflation by around 80 basis points in the first two years

and this impulse dies down speedily after that period. Ninety five percent confidence

interval shows that this impact is statistically significant for two and a half years.

Unanticipated to real private sector credit on the other hand has negligible impact on

inflation. Besides economic insignificance, the confidence interval shows that this

impact is statistically insignificant.

Robustness Check

In order to check the robustness of our results, we augmented the tri-variate VAR

with other potential determinants of inflation. The variables set was broadened to


21

include global oil prices and exchange rate.. The result of this VAR was not much

different from tri variate VAR (see Figure 4 and Figure 5) which suggest that our tri-

variate VAR results are robust to inclusion of new variables in the system.

To sum up, IRF analysis of inflation shows real money balances has statistically

significant positive impact on inflation. Further, some components of money like

NDA and budgetary borrowing shocks have more pronounced impact on inflation. In

contrast, NFA shock and credit to private sector has statistically insignificant impact

on inflation. Thus while assessing the plausibility of meeting inflation target,

monetary authority should not only look at the aggregate money balances trend but

also its composition.

5.2.2Analysis of Variance Decomposition

Variance decomposition of inflation shows that real money balances are are the

important determinant of inflation in Pakistan. Specifically, these balances explain

around 20 percent of the total variation in inflation (Figure 6). However, this impact

varies across different components of real money balances. For instance, NDA

explains around 7.0 percent of the total variation in inflation followed by net

budgetary borrowing from the banking system which explains 5.04 percent of the

total variation in inflation. The share of the remaining components of broad money i.e

NFA and private sector credit in explaining variation in inflation is negligible.


22

It may also be mentioned here that results show that global oil prices, exchange rate

and GDP growth explain a considerable part of the variation in inflation in Pakistan.

In particular, oil prices, exchange rate and GDP growth accounts for around 15

percent, 10 percent and 4 percent variation in headline inflation.

6. Conclusion

This study analyzes the relationship between money growth and inflation from two

perspectives. The first one focuses on the relationship between broad money growth

and inflation while the second focuses on the growth in components of broad money

and inflation.

The study attempts to answer this question with the help of parametric and non-

parametric approaches. In the first case, the author uses event study approach while in

the latter case a sophisticated econometric technique called Structural VAR is

benefitted from. The study uses the annual data ranging from 1980-2016

The results of both the event study and structural VAR show that monetary aggregates

are still an important determinants of inflation in Pakistan. Changes in monetary

aggregates is an important leading indicators for future movements in inflation.

Further, analysis of compositional changes in monetary aggregates is also quite useful

for assessing the objective of price stability. For instance, government borrowings

from the banking system to finance fiscal deficit has very pronounced impact on

future inflation. On the contrary the study found that expansion in NFA has


23

dampening impact on inflation. To sum up, monetary expansion driven by fiscal

deficit financing seems to be most inflationary. On the other hand, monetary

expansion driven by private sector credit and buildup in NFA appears to be least

inflationary.

The above findings suggest that though State Bank of Pakistan has shifted to interest

rate targeting from money targeting and is building the models for monetary policy

analysis where money has lesser role, monetary aggregates are still relevant for

assessing the plausibility of achieving the objective of price stability.

Equally important is the analysis of compositional changes in monetary aggregates. In

the episodes where monetary expansion is driven by fiscal deficit financing

(government borrowings from the banking system) tightening monetary policy alone

may not be sufficed to tame inflationary pressures in Pakistan. This is because

government borrowings from the banking system are largely driven by the

government fiscal needs, which are less sensitive to changes in policy rate. As a result,

monetary policy tightening affect the money demand largely through reduction in

credit to private sector which is relatively less inflationary component of money. Thus

for the monetary policy to deliver, coordination between monetary and fiscal policy

and fiscal consolidation (curtailment of fiscal expansion) is also must.

These findings may also be used to construct a more useful weighted average

monetary index for assessing the objective of price stability. Currently, there is a


24

fashion of constructing monetary aggregate index from liability side. Specifically,

different monetary liabilities are weighed according to their liquidity content and then

a weighted monetary index is constructed. We argue that this type of index can also

be constructed from assets side of money. Different monetary assets could be weighed

according to their inflationary impact and then a weighted monetary index be

constructed.


25

References

Abbas, K. and F. Husain (2006). “Money, Income and Prices in Pakistan: A Bivariate

and Tri-variate Causality.” South Asia Economic Journal, 7(1): 55-65.

Bernanke. S.S and Blinder. A.S (1990), “The Federal Fund Rate and the Transmission

of Monetary Policy.” NBER Working Paper No 3487

Beyer, A. Fischer.B and Julian.V.L. (2007). “Money Demand Stability: Implications

for the Usefulness of Money in Monetary Policy.” Mimeo, European Central Bank

Christiano, L. J, Eichenbaum.M.S and Evans.C. L(2001), “Nominal Rigidities and

the Dynamic Effects of a Shock to Monetary Policy”. NBER Working Paper No 8403

Dewald, William G. 1998. “Money Still Matters.” Federal Reserve Bank of St. Louis

Review 80 (November/December): 13–24.

Fisher, B and Pill, H (2010). “Improving Models of Euro Area Money Demand”

Enhancing Monetary Analysis, Chap. 3.Frankfurt: European Central Bank,

pp.131-55.

Fischer, B; Lenza. M; Pill. Huw and Reichlin, L (2007) “Money and Monetary

Policy: The ECB Experience 1999-2006.” Mimeo, European Central Bank

Friedman, B.M (1990). “Targets and instruments of Monetary Policy” Handbook of

Monetary Economics Vol.2 Amsterdam: North-Holland pp 1185-1230

Friedman, B.M and Kuttner.K.N (1992), “Money, Income, Prices, and Interest Rates.”

The American Economic Review Vol.82 PP 472-492

Husain. F and Rashid. Abdul (2006). "Significant Shift in Causal Relations of Money,

Income, and Prices in Pakistan: The price Hikes in the Early 1970s," PIDE-Working

Papers

McCallum.B.T and Nelson. E.(2010). “Money and Inflation: Some Critical Issues”

Federal Reserve Board, Washington, D.C.

Moinuddin (2009). “Choice of Monetary Policy Regime: Should SBP Adopt Inflation

Targeting?” SBP Research Bulletin, 5(1): 1-30, Karachi. SBP

http://ideas.repec.org/p/pid/wpaper/20068.html



http://ideas.repec.org/s/pid/wpaper.html




26

Omer, M., and O. F. Saqib (2009). “Monetary Targeting in Pakistan: A Skeptical

Note.” SBP Research Bulletin, 5(1): 53-81. Karachi. SBP.

Poole, M. (1970), “Optimal Choice of Monetary Policy Instrument in Simple

Stochastic Macro Model” Quarterly Journal of Economics, Vol 84(2) : 197-216

Qayyum, A. (2006). “Money, Inflation and Growth in Pakistan.” Pakistan

Development Review,

45: 203–212.


27

Table 3: ADF Test Results

ADF Test

Critical Value

Statistics (5 %) Probability Conclusion

Level

GDP growth

-3.5

-2.9

0.005

I(0)

Real M2 growth -5.5 -2.9 0.000 I(0)

Inflation -4.0 -2.9 0.004 I(0)

Real NDA growth -5.6 -2.9 0.000 I(0)

Real NFA growth -5.3 -2.9 0.000 I(0)

Real Budgetary Borrowing growth -5.3 -2.9 0.000 I(0)

Real oil price growth -5.3 -2.9 0.000 I(0)

Real Exchange rate growth -5.5 -2.9 0.000 I(0)

Real Private Sector Credit growth -3.0- -2.9 0.04 I(0)


28

Lower Infla tion U pper

1 2 3 4 5 6 7 8 9 10

Figure 4: Tri-Variate VAR: Impulse Response of Inflation to One Standard Deviation

Unanticipated Shock in Real Money Growth and its Components

Real Broad Money Expansion Real Net Domestic Assets Expansion

2.0

1.5

Lower Inflation Upper

2.0

1.5


1.0 1.0

0.5 0.5

0.0

-0.5

1 2 3 4 5 6 7 8 9 10

0.0

-0.5

1 2 3 4 5 6 7 8 9 10

-1.0

Real Public Sector Borrowing Growth

-1.0

Real Net Foreign Assets Expansion

2.0

1.5


2.0

1.5


1.0 1.0

0.5 0.5

0.0

-0.5

1 2 3 4 5 6 7 8 9 10

0.0

-0.5

1 2 3 4 5 6 7 8 9 10

-1.0 -1.0

Real Private Sector Credit

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00


29

Figure 5: Five-Variate VAR: Impulse Response of Inflation to One Standard Deviation

Unanticipated Shock in Real Money Growth and its Components

Broad Money Expansion Net Domestic Assets Expansion

2

1.5

1

0.5

0

-0.5

-1

-1.5

-2


1 2 3 4 5 6 7 8 9 10

2

1.5

1

0.5

0

-0.5

-1


1 2 3 4 5 6 7 8 9 10

Public Sector Expansion

2

1.5

1

0.5


Net Foreign Assets Expansion

2

1.5

1

0.5

0


0

-0.5

1 2 3 4 5 6 7 8 9 10

-0.5

-1

1 2 3 4 5 6 7 8 9 10


30

Figure 6: Variance Decomposition of Inflation

Real Money Balances Explains around 20 % of variation in Inflation

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1 2 3 4 5 6 7 8 9 10

global oil GDP Exchange Rate Inertia Real Money balances

Real NDA Explains around 7 % of variation in Inflation

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1 2 3 4 5 6 7 8 9 10

global oil GDP Exchange Rate Inertia Real Money balances (ndar)

Real Government Borrowing Explains around 5 % of variation in Inflation

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1 2 3 4 5 6 7 8 9 10

global oil GDP Exchange Rate Inertia Real Money balances (Govt Borowing)

Real NFA Explains around 1 % of variation in Inflation

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1 2 3 4 5 6 7 8 9 10

global oil GDP Exchange Rate Inertia Real Money balances (nfar)

Real Private Sector Credit Growth Explains around 0.3 % of variation in Inflation

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

1 2 3 4 5 6 7 8 9 10

global oil GDP Exchange Rate Inertia Real Money balances (Psc)

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