Inflation in Pakistan
ABSTRACT This paper examines the factors that explain and help forecast inflation in Pakistan. A simple inflation model is specified that includes standard monetary variables (money supply, credit to the private sector), an activity variable, the interest and the exchange rates, as well as the wheat support price as a supply-side factor. The model is estimated for the period January 1998 to June 2005 on a monthly basis. The results indicate that monetary factors have played a dominant role in recent inflation, affecting inflation with a lag of about one year. Private sector credit growth and broad money growth are also good leading indicators of inflation which can be used to forecast future inflation developments.
The Pakistan Development Review
45 : 2 (Summer 2006) pp. 185–202
Inflation in Pakistan
MOHSIN S. KHAN and AXEL SCHIMMELPFENNIG
This paper examines the factors that explain and help forecast inflation in Pakistan. A simple inflation model is
specified that includes standard monetary variables (money supply, credit to the private sector), an activity variable, the
interest and the exchange rates, as well as the wheat support price as a supply-side factor. The model is estimated for the
period January 1998 to June 2005 on a monthly basis. The results indicate that monetary factors have played a dominant
role in recent inflation, affecting inflation with a lag of about one year. Private sector credit growth and broad money
growth are also good leading indicators of inflation which can be used to forecast future inflation developments.
JEL classification: E31, C22, C32
Keywords: Inflation, Pakistan, Leading Indicators, Forecasting, Monetary Policy
After remaining relatively low for quite a long time, the inflation rate accelerated in Pakistan starting
in late 2003. Following the 1998-99 crisis, inflation was reduced to below 5 percent by 2000 and remained
stable through 2003. Tight monetary policy combined with fiscal consolidation appears to have contributed to
this low-inflation environment.1 Figure 1 shows that inflation follows broad money growth and private sector
credit growth closely with a lag of about 12 months. With monetary growth picking up, inflation followed
and increased sharply in late 2003, peaking at 11 percent year-on-year in April 2005. Average annual
inflation stabilised around 8 to 9 percent by September 2005, and has receded somewhat since then.
Controlling inflation is a high priority for policy-makers. High and persistent inflation is a regressive
tax and adversely impacts the poor and economic development. The poor have little options to protect
themselves against inflation. They hold few real assets or equity, and their savings are typically in the form of
cash or low-interest bearing deposits. Thus, this group is most vulnerable to inflation as it erodes its savings.
Moreover, high and volatile inflation has been found to be detrimental to growth [e.g.,
Mohsin Khan <email@example.com> is Director of the Middle East and Central Asia Department of the International Monetary
Fund. Axel Schimmelpfennig <firstname.lastname@example.org> is an Economist in the International Monetary Fund’s Middle East and
Central Asia Department.
Author’s Note: The views expressed in this paper are those of the authors and do not necessarily represent those of the
International Monetary Fund or its policy. This paper draws on previous work by Khan and Schimmelpfennig, “Inflation in Pakistan:
Money or Wheat?”, published in the State Bank of Pakistan’s Research Bulletin–Papers and Proceedings Vol. 2, No. 1, available at
http://www.sbp.org.pk/research/ bulletin/2006/Inflation_in_Pakistan_Money_or_Wheat.pdf, and in Bokil and Schimmelpfennig “Three
Attempts at Inflation Forecasting,” available as IMF
1According to the State Bank of Pakistan (SBP) a change in the methodology of deriving the house rent index may also be partly
responsible for the observed slowdown in headline inflation.
Working Paper 05/105 at http://www.imf.org/
Khan and Schimmelpfennig
authorities; and IMF staff calculations.
Khan and Senhadji (2001)] and financial sector development [e.g., Khan, Senhadji, and Smith (2006)]. High
inflation obscures the role of relative price changes and thus inhibits optimal resource allocation.
Understanding the factors that drive inflation is fundamental to designing monetary policy. Certainly in
the long run, inflation is considered to be—as Friedman (1963) stated—always and everywhere a monetary
phenomenon. Workhorse models of inflation typically include monetary variables, such as money growth,
real GDP, the interest rate, and the exchange rate as explanatory variables. Some authors have also pointed to
supply side developments in explaining inflation. This structuralist school of thought holds that supply
constraints that drive up prices of specific goods can have wider repercussions on the overall price level. For
example, in Pakistan, increases in the wheat support price have frequently been blamed for inflation.2
This paper finds that monetary factors are the main drivers of inflation in Pakistan, while other typical
explanatory variables play less of a role. We specify a simple inflation model that includes standard monetary
variables (money supply and credit to the private sector), the interest rate, the exchange rate, an activity variable,
as well as the wheat support price as a supply-side factor. The model is estimated with monthly data for the
period January 1998 to June 2005. The results indicate that monetary factors have played a dominant role in
recent inflation, affecting inflation with a lag of about one year. Monetary factors are also well-suited to forecast
inflation in a leading-indicator type model.
The remainder of the paper is organised as follows. Section II reviews the relevant literature and
introduces a stylised model to structure the analysis. Section III estimates the model and assesses the roles for
explaining inflation played by monetary factors and other variables. Section IV presents a leading indicators
model to forecast inflation, and Section V provides some conclusions.
2The acceleration of inflation in late 2003 coincided with two increases in the wheat support price in September 2003 and in
September 2004, which has re-opened the debate whether the wheat support price was driving inflation in Pakistan [Khan and Qasim
(1996) and Sherani (2005)].
Credit growth (lagged 12 months, right axis)
Broad money growth (lagged 12 months, right axis)
Fig. 1. Pakistan: Inflation and Monetary Growth, 1999:1–2005:6
(Average annual growth in percent)
Inflation in Pakistan
II. BASIC ELEMENTS OF THE MODEL
Several studies highlight the role of monetary factors for inflation in Pakistan.3 For example, Khan and
Qasim (1996) find that overall inflation is only determined by money supply, import prices, and real GDP.
The empirical evidence is inconclusive regarding the role of the exchange rate. Choudhri and Khan (2002) do
not find evidence of exchange rate pass-through in a small VAR analysis, while Hyder and Shah (2004) find
some evidence of exchange rate pass-through using a larger VAR. Some authors have emphasised
structuralist factors in explaining inflation in Pakistan.4 Khan and Qasim (1996) find food inflation to be
driven by money supply, value-added in manufacturing, and the wheat support price.5 Non-food inflation is
determined by money supply, real GDP, import prices, and electricity prices. Sherani (2005), referring to this
work, finds that increases in the wheat support price raise the CPI index (but not necessarily inflation). He
also argues that the high levels of inflation in 2005 largely resulted from a monetary overhang that was built
up by loose monetary conditions.
We start our stylised model from a monetarist perspective. Agents hold money for transaction
purposes, as a store of value, and for speculative purposes. For a constant velocity (ν), inflation ( p & ) results if
money growth (m & ) exceeds real GDP growth ( y & ). The opportunity cost of holding money, that is the interest
rate r, reduces money demand and thus inflation. Moreover, financial deepening and innovations enable
agents to use alternative monetary instruments in lieu of cash. Thus, the velocity of a particular monetary
aggregate, say M2, changes if agents switch from cash or demand deposits to instruments included only in
M3. In an open economy, headline inflation can also be affected by movements of the exchange rate (e).6 We
also allow for the wheat support price (w) as a structuralist factor to drive inflation. The general open-
economy monetary model (incorporating a supply-side variable) is then given by
… … … … … … (1)
where lower case letters denote the natural logarithm of a variable and a dot over a variable denotes the first
derivative with respect to time.
For non-stationary time series, Equation (1) only reflects short-run relationships as the variables are in
(log) first differences, and the equation does not include a cointegrating relationship. However, the aspects of
the model that reflect monetarist thinking will tend to be long-run relationships, and the model can be easily
be rewritten in levels and in an error correction representation to differentiate between short-run and long-run
3For a comprehensive survey of empirical studies on Pakistan [see Bokil and Schimmelpfennig (2005)].
4Structuralist models of inflation emphasise supply-side factors as determinants of inflation. They emerged in the 1950s as part
of the structuralist theories of development promoted by Prebisch [see Bernanke (2005)]. In these models, inflation is driven by
developments and bottlenecks on the real side of the economy. Food prices, administered prices, wages, and import prices are considered
sources of inflation. Structuralist models assume that such factors have to be accommodated by monetary policy-makers because they are
determined outside the monetary sphere. Monetary developments in themselves are given little importance as independent determinants
5It is hardly surprising that changes in the wheat support price affect the food price index, given that wheat products account for
14 percent of the index. However, this does not automatically imply that headline inflation is affected by changes in the price of one
6Import prices could also play a role, in particular if the exchange rate is pegged. Unfortunately, import prices are not available
at a monthly frequency, but since Pakistan had a flexible exchange rate regime during our sample period, import prices should be less
important than in previous years.
Khan and Schimmelpfennig
III. EMPIRICAL RESULTS
We estimate the basic model in growth rates as well as in log levels. Since our sample extends over a
crisis period and subsequent wide ranging economic reforms as well as a growth take-off, it may be difficult
to discern long-run relationships from the data due to structural changes and non-constant parameters.
However, we would still expect short-run relationships to reflect our proposed model structure. Therefore, as
a first step, we estimate Equation (1) to gain an understanding of some basic relationships and short-run
dynamics.7 In the second step, we estimate the model as a vector error correction model (VECM) in log-
levels to investigate whether we can find a cointegrating vector that would provide information about long-
(a) Data and Sample
Our database covers the period January 1998 to June 2005 on a monthly basis. The choice of sample
reflects a trade-off between having sufficient observations and avoiding structural breaks that would
complicate the empirical analysis. Banking sector reforms were initiated in 1997 and pursued vigorously after
1999, leading to increased intermediation. Financial deepening also occurred as confidence returned in the
aftermath of the 1998-99 crisis and with the new government restoring macroeconomic stability. Taken
together, this implies that the monetary transmission mechanism has evolved and money demand has possibly
shifted over the sample period which may lead to nonconstant parameters, in particular with respect to long-
The definitions of the data utilised are:
• CPI: overall consumer price index—the percentage change of which is also termed “headline
• Monetary variables: Broad money; private sector credit; and the 6-month treasury bill (T-bill) rate
(the SBP’s key policy rate).
• Activity variables: interpolated real and nominal GDP (12-month moving average of the fiscal year
GDP data);8 and the large scale manufacturing index (LSM).
• Exchange rate: nominal effective exchange rate (NEER).
• Wheat support price: guaranteed minimum government purchase price.
The basic correlations between the variables are shown in Table 1.
The log levels of all variables are non-stationary. Most variables are integrated of order one (Table 2).
However, somewhat surprisingly, our interpolated real and nominal GDP series are integrated of order two.
This would suggest that our GDP series cannot be part of a long-run cointegrating relationship with other
variables that are only integrated of order one. Alternatively, the LSM may be a meaningful proxy for the
Data for Pakistan is subject to overlapping seasonality stemming from Gregorian calendar effects
(including agricultural seasonality) and Islamic calendar effects. Riazuddin and Khan (2005) construct
variables to address Islamic seasonality. For regressions based on growth rates, we control for seasonality by
using 12-month moving averages. In Bokil and Schimmelpfennig (2005), we show that this is sufficient to
take account of both sources of seasonality. The approach has the advantage of requiring no additional
7Note that this model may be mis-specified if we have non-stationary data and there exists a cointegrating vector.
8GDP data is available only at annual frequency.
9The correlation coefficient between the annual LSM index and annual real GDP is 0.97 which suggests that a 12-month moving
average of the LSM index is probably a reasonable proxy for monthly real GDP.
Inflation in Pakistan
regressors. However, for regressions based on log levels, we include monthly dummies and the Islamic
calendar control variables used in Riazuddin and Khan (2005).10
(b) CPI Inflation
We first analyse the impact of changes in the explanatory variables on headline inflation. We estimate
two variants of our stylised model using either broad money or private sector credit to capture the impact of
monetary policy. The models are estimated using the PcGets routine in PcGive which automatically tests
down a general model.11 In our case, we include 12 lags of all variables in the general model. In principle, the
resulting specific model can then include individual lags of the variables from the general model, or exclude
We focus on summary coefficients that give the direction of influence of a particular regressor after all
dynamics have played out. The estimated specification is an autoregressive distributed lag model (ADL) that
can be written as:
( ) ( )
… … … … … … (2)
where x is the vector of independent variables. A(L) and B(L) are lag polynomials that take the form:
The ADL can be re-written as:
. … … … … … … … (3)
10We thank R. Riazuddin and M. Khan for kindly providing their data to us. In some specifications, the control variables for calendar
effects can be dropped.
11The routine is described and illustrated in Hendry and Krolzig (2004).