Final Thesis on the Determinants of Inflation in Pakistan

CHAPTER NO 1

INTRODUCTION

1

Abstract

This study attempts to investigate the effects of import price and participated money supply on

inflation in Pakistan. The model is estimated for the period 1976 to 2005 on a yearly basis. This

paper employs the cointegration and error correction model (ECM) methodology to estimate the

long-run relationship between the import price, money supply and inflation in Pakistan.

Keywords: Inflation, Money Supply and Import Price.

2

Chapter 1

Introduction

Our study will be focused at the various aspects of inflation in Pakistan from a local and global viewpoint.

Pakistan remained prominent figure among the few developing countries which attained remarkable

economic growth and poverty reduction in the first forty years of its existence. GDP remained up to 6

percent per annum and poverty incidence lowered from 46 percent to 18 percent until late 1980. Inflation

rate remained low and despite high population, growth per capita incomes had almost doubled. The

decade of 1990 was not proved a favorable for the economy of Pakistan and the whole situation was

reversed. Growth rate was lowered to an average 3 to 4 percent and poverty increased to 33 percent of the

population. Inflation was in double digits. Inflation can be defined as the persistent rise in the general

price level across the economy over time. Mild inflation is considered to be desirable for economic

growth. However, high and variable inflation, in general, leads to uncertainties in income and expenditure

decisions of the different groups of the society. The present study is a modest attempt to answer these

questions. The basic objective of the study is to identify the factors influencing inflation in Pakistan. It

includes the following specific objectives:

To review major models of inflation and identify the appropriate model for Pakistan.

To identify the short-term and long term relationship of inflation with the factors after their

identifications; and

To analyze the impact of determining variables in inflation.

3

Inflation or price inflation is a rise in the general level of prices of goods and services in an economy over

a period of time. Inflation can be controlled by Monetary Measures. Several supply side and demand side

factors could be responsible for this surge in inflation. Inflation can be a result of shocks to the supply of

certain food items and to world oil markets. Rising oil prices can fake risk of increase in prices of almost

all other commodities of the consumer case. Such supply-side shocks are very unstable and can cause

large fluctuations in food and oil prices. The effects of this on overall inflation at times can be so

excessive that these cannot be countered through demand management, including monetary policy.

However, greater emphasis in the recent debate on inflation remained on the demand side factors. So,

inflation is an important economic indicator. There are various indicators which measure the inflation,

such as; import price; money supply; gross domestic product (GDP) deflator and so on. But I took two

variables import price and money supply in Pakistan.

.

Definition:

1.1 Inflation

“An increase in the prices of goods and services that is generally expressed as an annual

percentage increase in the Consumer Price Index, as compiled by the Department of Labor”

“ Inflation is a rise the general level of prices and services in an economy over a period of time”

1.2 Money Supply

“Money Supply or money is the total amount of money avaible in an economy at a particular

point in time it usually include currency in circulation and demand deposits.”

4

1.3 Import Price

“An import price index measures changes in the prices of imports of merchandise into a country.

The index numbers for each reference period relate to prices of imports landed into the country

during the period”.

1.4 Causes of inflation in Pakistan:

Press information department of Pakistan in 2005 state some causes of high inflation in Pakistan

including:

Political instability.

Higher duties and taxes.

Decelerating economic growth.

Loose monetary polices.

1.5 Purpose of the study

The purpose of this study is will be to test how inflation is effected by the import price and

money supply. If Money Supply and Import Price are increase then it will directly effect the

inflation. The data of all above variables is taken from the World Develop Indicter (WDI), which

is a publication of international monetary fund (IMF), from publications of word bank, annual

economics surveys by the government of Pakistan and the publication of State Bank of Pakistan.

5

1.6 Research Question and Hypothesis:

Main question:

What is the relationship between Inflation, import price and Money Supply?

Sub questions:

Relationship between Inflation and Import Price.

Relationship between Inflation and Money Supply.

1.7 Hypothesis:

Ho: There is no Relationship between Inflation, Money Supply, GDP Growth and Import Price.

H1: There is Relationship between Inflation, Money Supply, GDP Growth and Import Price.

6

CHAPTER NO 2

Literature review

7

Chapter 2

Literature review

Abdul Aleem et.al (2007) focuses on the identification of the main determinants of recent inflation trends

using the data from the 1972 to 2005 period. The study evaluates the role of different factors such as

government sector borrowing, demand relative to supply, private sector credit, imported inflation,

exchange rate, total tax revenue of the government, adaptive inflation expectations and wheat support

price in explaining inflation. By applying ordinary least square method and verifying results through

Breusch-Godfrey Serial Correlation LM and Augmented Dickey-Fuller tests, it is found that to overall

impact of fiscal policies on inflation was not significant and rather the direct part of taxes was dominant

in putting downward pressure on prices. So on the basis of our analysis, it can be safely stated that

expansionary monetary policy not only contribute in promising GDP growth but it also led to the rise in

consumer prices.

Wasim Shahid (2006) investigated “Why has inflation been high in some of the periods?”For this

purpose he used the data for the period1975:03 to 2003:02. Taken from International Financial Statistics

(IFS) and that on real GDP from Kemal and Arby (2004).There are at least three possible reasons for it;

monetary policy actions, supply side factors and trading partner countries. By using Near-VAR approach

and ordinary least square (OLS) method we draw result from the study that inflation responds positively

to monetary shocks. It means money is an important determinant of inflation in Pakistan. This result is in

line with that of Khan and Schimmelpfennig (2006). Also the study suggests that there is a need for a

study that investigates the determinants of inflation variability by considering all the three factors

discussed above.

Qasim et.al (1996) conducts a study in which the on the whole inflation equation and its two significant

components that are CPI food price inflation and CPI non-food price inflation equations. The cause for 8

disaggregating of overall inflation is that an aggregate inflation may cover the important information

about the factors influencing current rise in inflation. They originate a defect in previous studies that is

the consideration of only non-stationary properties of the related variables and regression of non-

stationary variables can reason superior regression problem so they have used affirmative technique

which is the better indicator of inflation than regression. A time series data from 1971 to 1994 is used to

estimate the equation. Co integration and error correction model are used to estimate the various price

equation using non-stationary properties of variables. Co integration model results suggest that the

general price level depend upon money supply domestic economic activity import price index and interest

rate. Dickey-Fuller and the Augmented Dickey-fuller unit root tests are used to determine the order of

integration of all the variables and all series of data are found to be stationary in first difference. A co

integration regression is estimated by using ordinary least squares. The result of multivariate regression of

overall inflation suggests that there is a strong role of money supply and frequent currency devaluation in

accelerating the inflation in Pakistan. So it can be concluded that there is a strong need for tightening of

the fiscal policy and reviving commodity-producing sectors, fiscal regulation and excess in raising prices

are the key to the success to control the expansion in the overall inflation rate in Pakistan.

Anjum et.al (1996) described the sustainability of fiscal policy in Pakistan and work out the sustainable

level of the deficit keeping stable economic growth, optimal inflation and interest on foreign loans in

view. Former studies have discussed the impact of fiscal deficits on economy but didn’t analyze it in

macroeconomics framework. The data from three time periods: the 1980’s, 1985 and 1993 is used and the

average of sustainable deficits of these time periods is estimated in alternative scenarios. An integrated

model is developed using different debt strategies to formulate alternative scenarios for fiscal deficits.

Required deficit reduction can be obtained based on sustainable rate of inflation, interest rate on loans and

by using prudent debt strategies (domestic and foreign). The model is used to find out the consistency

between fiscal deficits, output growth rate of inflation and other macroeconomics variables. The model is

estimated by using different cases that are developed by combining different variables alternatively to

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highlight different perspectives. Using these cases the sustainable deficits during the above mentioned

time periods are analyzed. It can be concluded that fiscal deficit need to be reduced for sustainability of

the fiscal system and for stable economic growth.

Kennedy et.al (2003) determine the key determinants of inflation in Ghana to know whether inflation is

a real sector issue or a monetary issue. The different theories proposed by different economists are

classified into two wide categories, the excess–demand theories in the category of expectations-

augmented Phillips curve and the cost-push theories which are currently termed

structuralisms/institutional theories of inflation. They used the data from 1970 to 2002.The excess-

demand theories argued that excess demand for goods and services over supply in an economy is the main

source of inflation. The technique that have been used to estimated the result was regression analysis

which sagest that the explanatory variables was not significant as some of the determining inflation

factors have not been included in the model.

Qayyum (2006) conduct a study in which he found that the monetarist’s proposition that money supply

has been the key determinant of inflation in Pakistan. He estimated the relationship between the rate of

inflation, money growth, growth in real income and growth in velocity in Pakistan. He used the data from

1960 to 2005. The result from the correlation analysis indicates that there is strong relationship between

the money growth and inflation. The correlation coefficient between the money growth and current real

GDP growth is 0.226 and its is 0.069 with previous year’s money growth and current year’s real GDP

growth. However it is statistically insignificant. The results lead us to say that money growth at first

round effect real GDP growth and at second round the money growth effects inflation in Pakistan.

Safdar.A & Omer.F (2009) investigate the effects of political instability on inflation in Pakistan. The

annual time series data has been used for the years 1951 to 2007 which generally covers the economic

and political environment of Pakistan. They recommend two different estimable models the first model

was the summary of the empirical evidence previously available on Pakistan economy and the second

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model stems from the ‘nonmonetary’ determinants of inflation literature. The dependant variable was

Inflation as the yearly growth rate of Consumer Price Index and to account for the historical impact of

inflation, inflation inertia, as one of the explanatory variables used one period lagged inflation. The

results of the ‘monetary’ model suggest that the effects of monetary determinants were rather marginal

and that they depend upon the political environment of Pakistan. The ‘nonmonetary’ model’s findings

explicitly establish a positive association between measures of political instability and inflation and it was

further confirmed on analyses based on interactive dummies that reveal political instability significantly

leading to high (above average) inflation.

Harris et.al (2004) found the work on financial development has brought a focus to what role it may

play in economic growth, focusing mainly on developed countries. Growth has also been explained in

terms of a negative effect from inflation. The relationship between inflation and growth with conflict in

empirical results. A candidate explanation for such difference can be categorized into to three reasons.

First, the econometric specification have often neglected the very important cross county unobserved

heterogeneity, and also have lacked time effect that account for trend-deviation. Secondly, the non-

linearity and parsimonious specification arising out of a single, comprehensive, theoretical growth model

has no taken into account. This paper presents an endogenous growth model that implies both a

signification, negative, non-linear inflation effect and an appropriate econometric specification. Third the

instruments to account for a possible endogenously of the inflation rate typically have not been

theoretically derived from the same self-continued model. They used the data from 1990 to 2002 for 13

transition countries on inflation, financial development and growth. Two models are specified. First the

Dawson model is presented. This includes the investment rate and financial depth but not inflation. The

second model is extended to include inflation plus other variables as related to a theory of endogenous

growth. They used of the money supply as the instrument is a theoretically given choice and it result in a

significant, non-linear, inflation growth effect in both OECD and APEC samples

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Robert.J (1960-1990) shows the relationship between the inflation and economic growth. He collected

the sample for around 100 countries while the sample period was from 1960 to 1990 to evaluate the effect

of inflation. The Annual inflation rates were computed from consumer price indices. The statistical test

that has been applied on the data was a system of regression equations in which many other determinants

of growth were held constant and the findings revealed that a likely channel by which inflation decreases

growth was through a reduction in the propensity to invest and that the estimated effects of inflation on

growth and investment were significantly negative when some plausible instruments were used in the

statistical procedures thus, there was some reason to believe that the relations reflect causation from

higher long-term inflation to reduced growth and investment. The researcher suggest that if a number of

country characteristics are held constant, then regression results indicate that an increase in average

inflation of ten percentage points per year reduces the growth rate of real per capita GDP by 0.2–0.3

percentage points per year and lowers the ratio of investment to GDP by 0.4–0.6 percentage points

although the adverse influence of inflation on growth looks small, the long-term effects on standards of

living are substantial.

Hanif et.al (2006) described the hypothesis of the Romer’s suggest that inflation is lower in small and

open economies for Pakistan economy. Different studies have been conducted before on inflation and

openness in context of Pakistan but no research work had been done and this is the first such evidence to

model the behavior of inflation by focusing on how more integration with the rest of the world affects

inflation in Pakistan economy. They used the time series data for the period 1973-2005. Inflation is a

complex process and it is very difficult to construct an empirical model for a country but key variables

influencing the inflation in Pakistan can be found so they consider the rate of money growth, real GDP

growth, and growth in Wheat Support Price and over night interest rate as explanatory variables. Firstly,

Augmented Dickey-Fuller (ADF) approach is used to test stationary of the times series used in the

analysis then the model is estimated using HAC estimator and all diagnostic tests are applied on the

equation. When equation passes these tests then a proxy for openness is included. It is tested that if

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openness has any significant impact on inflation process in Pakistan in the presence of explanatory

variables found significant in the estimated equation. While controlling for all the standard theoretical

determinants of inflation it is concluded that openness has significant negative impact on the domestic

price growth and hence result supports the Romer’s hypothesis.

Vogel (1974) developed a monetary model for explaining inflation in Latin America. The author's model

considered the rate of inflation as a dependent variable and the percentage change in money supply during

current and previous years percentage change in real income during current period and change in inflation

rate lagged by one year and two years as explanatory variables. Vogel concluded that the coefficients of

(Mt and Mt-1) are highly significant and thus indicate that an increase in the rate of growth of money

supply causes a proportionate increase in the rate of inflation within two years. At the same time the rate

of inflation is found to be inversely influenced by the growth rate of real income. The rate of inflation is

not found to be so much influenced by (Pt-1– Pt-2), rather inflation rate lagged by one year, P t-1 has

much influence on the current rate of inflation. The increase in the last equation above is mainly

attributed to the high significance of P t-1.

Schimmelpfennig et.al (2006) examines the factors and assist forecast inflation in Pakistan.

Controlling inflation is a high priority for the policy makers as high inflation obscures the role of relative

price changes and thus inhabits the optimal resource allocation. The simple inflation model is specified

that includes standard monetary variables, the interest rate, the exchange rate, an activity variable and a

wheat support price as the supply-side factor. The monthly data from January 1998 to June 2005 is used

to conclude the results that monetary factor has a dominant role in recent inflation. The basic model used

is estimated both in growth rates and log levels.

Saqib et.al (2009) conduct a study in which investigation of the effects of political instability on

inflation of Pakistan. Most of the studies conducted earlier have not taken into account the simultaneity

that is associated with ordinary least square (OLS) model and hence lead to inconsistent results. The data

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from 1951-2007 is used to investigate the effects of political instability on inflation of Pakistan. The two

models namely Monetary and Non-Monetary are used. The prediction from Fiscal Theory of Price Level

(FTPL) and PEMP literature is used for investigation. The weak-form FTPL and strong-form FTPL are

used that argued that the price level and hence the inflation is caused by budgetary policies of fiscal

authorities. Two predictions from PEMP literature namely ‘political instability and Deficit Bias’ and war

of attrition are used in the investigation.

Fischer, Sahay and Végh (2002) point out that evaluates the impact of non-monetary inflation

determinants in a world sample comprised by 97 countries over the period 1975-2005. The dependent

variable is the rate of inflation for country in period which is normalized as to avoid giving too much

influence to outlier episodes of high inflation episodes, and independent variables are high inflation

episodes, monetary regimes, structural and institutional variables, cyclical variables, and openness. The

writers point out that there are several reasons to isolate these extreme but infrequent episodes: (a)

hyperinflations are very costly and countries are not willing to tolerate them for more than very few years

or even for only some months. Hence, some hyperinflation episodes may not be accounted for by annual

datasets. (b) Linear estimation models tend to severely over-estimate the impact of inflation on

macroeconomic performance compared estimations using samples of countries where this phenomenon is

absent. The results show the relevance of disciplinary effects in lowering inflation. First, inflation

targeting is estimated to lower inflation when taking as control group all non-inflation targeters for which

there is available information on macroeconomic variables, even after controlling for persistence and

several other determinants of inflation. A different interpretation would conclude that positive supply

shocks that help lower inflation are more prone to be found in developing countries, which is also very

appealing. Finally, we fail to find robust support to the idea that foreign output gap would influence local

inflation for either the short-run or long-run inflation regression models.

Khan and Hussain, 2005 describe a reasonable rate of inflation, around 3 to 6 percent for Pakistan is often

viewed to have positive effects on the economy of pakistan. This study, adopting an econometric

14

framework, focuses on the identification of the main determinants of recent inflation trends. Using data

from the 1972-73 to 2005-06 period, applying ordinary least square method and verifying results through

Breusch-Godfrey Serial Correlation LM and Augmented Dickey-Fuller tests, it finds that the most

important determinants of inflation in 2005-06 were adaptive expectations, private sector credit and rising

import prices. Whereas, the fiscal policy’s contribution to inflation was minimal. The quantitative

analysis reveals that the most significant factors which explain 8 percent inflation in 2005-06 were

inflation expectations, private sector credit (a significant part of asset side of money supply) and imported

inflation. Overall impact of fiscal policies on inflation was not significant and rather the direct part of

taxes was dominant in putting downward pressure on prices. Government sector borrowing also did not

contribute in the rise in prices in 2005-06, though it did contribute in 2004-05. The policy of keeping

stability in the exchange rate was successful in holding the exchange rate from putting further pressure on

prices. The role of wheat support/procurement price and the other unexplained factors were also

insignificant.

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CHAPTER NO 3

Theoretical Framework

16

Chapter 3

Theoretical FrameworkInflation can be explain and classified on the biases of different factors that cause inflation. It is a very hot and

burning topic in all over the world and present era. Every country wants to control it. Through different

measuring tools we can control inflation. Besides this different studies have been conducted and examine by the

different researchers regarding the inflation targeting strategies and they used different techniques and

methodologies and approaches to explore the impacts of inflation targeting on their economies. Also discussed

the independent variables and find out the relation between two or more variables and further discussed which

variable is mostly effect the inflation economy.

Independent variables:

Money Supply Import Prices

There are different theories of inflation and here we discussed the two main theories that is Demand Pull

Theory and Cost Push Theories. And further discussed the causes of inflation in these theories one by one.

3.1 Demand Pull Theory

Demand Pull inflation occurs due to increase in the demand in the economy is called when consumption

of a particular product are increase the demand also increase if the supply of that particular product is lacking.

So at this stage the demand and supply disequilibrium occurs and due to shortage of these goods people want to

purchase at any prices level. So the result is pries increases and leads to inflation. In demand pull inflation we

discussed two main causes which badly affect the Pakistan economy.

Money Supply

17

Money supply also affects the inflation rate of any economy. Money supply is only occur when the loose

monetary policies of the state bank and its wrong policies. Georgios Karras (2007) said that it’s also shown that

money growth has positive and lasting effects on inflation but possibly will affect output only in the short run or

in the long run. Money is probably neutral.

3.2 Cost Push Inflation

Cost push inflation occurs when the increase in cost of production. Cost of production consist of cost of direct

material, direct labor, and factory overhead and financial administrative and selling expenses also included in it.

So if the cost of production increases the will also increases the prices of product and services to maintain their

profitability. In cost push inflation we discussed two main causes of inflation which are given below.

Import Prices

Devaluation makes our currency cheap in terms of foreign currency. It also makes all those good cheap

which price in terms of rupees and all those goods prices are high which deals in term of dollar or foreign

currency. As a result export price fall and imports price rise. The purchase of imported raw material, goods and

services price will also increase as compare to the domestic cost of production and that is the main cause of

inflation in Pakistan.

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Import price

Money supply

Inflation

Theoretical Framework

In my study, I am trying to find out the impacts of money supply and import price on the inflation. In this model, money supply and import price is independent variable and inflation is dependent variable. Modern electronic system will have a positive or negative impact on the banking growth.

Dependent Variable

Inflation

Independent Variables

Import Price

Money Supply

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CHAPTER NO 4

Data & Methodology

20

Chapter 4

Data & MethodologyThe Variables which are used for study are Inflation, Money supply and Import prices.

Inflation (Dependent Variable)

Symbol Used: Inflation (INF)

Money Supply (Independent Variable)

Symbol Used: Money Supply (MS)

Import Price (Independent Variable)

Symbol Used: Import Price (MP)

In the study we want to investigate the correlation and regression/cointegration relationship

between ‘Inflation and Money Supply’ and ‘Inflation and Import Price’ in Pakistan long run as

well in short run. So, in the study the Inflation used a dependent variables and Money Supply

and Import Price as the independent Variables. For the research the annual data will be used on

Inflation, Money Supply and Import Price for the period of 1976 to 2005. As the purpose of the

study is to investigate the correlation relationship between ‘Inflation and Money Supply’ and

‘Inflation and Import Price’ in Pakistan in long run so we collect annual data from 1976 to 2005

form Pakistan for the research. We used the data of 30 years as we want to investigate the

macroeconomics impact of Money Supply and Import Price on Inflation. The data of all above

variables is taken from the international financial statistics (IFS), which is a publication of

21

international monetary fund (IMF), from publications of word bank, annual economics surveys

by the government of Pakistan and the publication of State Bank of Pakistan.

4.1 MethodologyEconomics Model

INFt = βo + β1MSt + β2GGDPt + β3IPt + ε t

A Stationary process

A stationary time series has constant mean. A constant variance and the covariance is

independent of time. Stationary process is essential for standard econometric theory. Without it

we cannot obtain consistent estimators.

First of all it will be checked that whether all above series are stationary or not? To test the

stationary property of all above series, the augmented Dickey-Fuller (ADF) test and Philips-

Perron test will be used. In statistics econometrics, an augmented Dickey-Fuller test (ADF) is a

test for unit root in a time series sample.

Testing Procedure

The testing procedure for the ADF test is

Δ INFt = βo +λ1INFt-1 + β1t +α1∆ INFt-1 + α2 ∆ INFt-2 + …...+ αp ∆ INFt-p + ε t

Where Δ INFt = INFt - INFt-1

Δ MST = βo +λ2MSt-1 + β2t +α1∆ MSt-1 + α2 ∆ MSt-2 + …...+ αp ∆ MSt-p + ε t

22

Where Δ MST = MSt - MSt-1

Δ MPT = βo +λ4MPt-1 + β4t +α1∆ MPt-1 + α2 ∆ MPt-2 +…...+ αp ∆ MPt-p + ε t

Where Δ MPT = MPt - MPt-1

Where βo is a constant, α is the coefficient on a time trend and ρ the lag order of the

autoregressive process. Imposing the constraints α = 0 and βo corresponds to modeling a random

walk and using the constraint βo = 0 corresponds to modeling a random walk with a drift.

By including lags of the order ρ the ADF formulation allows for higher-order autoregressive

processes. This means that the lag length ρ has to determined when applying the test. One

possible approach is to test down from high orders and examine the t-values on coefficients.

The unit root test is then carried out under the null hypothesis γ = 0 against the alternative

hypothesis of γ < 0. Once a value for the test statistic.

DFt =

γSE (γ )

Is computed it can be compared to the relevant critical value for the Dickey-Fuller Test. If the

test statistic is greater (in absolute value) than the critical value, then the null hypothesis of γ =

0 is rejected and no unit root is present.

Following are the hypothesis that will be checked by ADF test.

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For checking the stationary property in time series of Inflation.

Hypothesis 1

H¿ 0 ¿¿¿: INFt is non-stationary, λ1= 0.

H1 : INFt is stationary, λ1< 0.

Hypothesis 2 for checking the series of Money Supply (MSt )

H¿ 0 ¿¿¿: MSt is non-stationary, λ2= 0.

H1 : MSt is stationary, λ2 < 0.

Hypothesis 3 for checking the series of Import Price (MPt )

H¿ 0 ¿¿¿: MPt is non-stationary, λ4 = 0.

H1 : MPt is stationary, λ4 < 0.

Decision rule:

If p – value > 2.10% value, ==> not reject null hypothesis, i.e. unit root exists.

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If p – value < 0.10% critical value, ==> reject null hypothesis, i.e. unit root does not exist.

Simple Co - Integression Analysis

When the time series are non- stationary, the simple cointegration test will be used between

Inflation and Money Supply and Inflation and Import Price individually.

And the scatter diagram/ line diagram will be drawn for seeing the relationship between Inflation

and Money Supply and Inflation and Import Price respectively.

Following is the Simple estimation equation for Inflation and Money Supply

INFt = α +β1MSt + ε t

Following is the Simple estimation equation for Inflation and Import Price

INFt = α +β3 MPt + ε t

Correlation:

The correlation is one of the most common and most useful statistics. A correlation is a single

number that describes the degree of relationship between two variables. The correlation test will

be done to check the correlation relationship between Inflation and Money Supply, Inflation and

Import Price.

Test of Goodness of Fit and Correlation:

25

We will test the overall explanatory power of the entire regression; this is accomplished by

calculating the coefficient of determination which is usually denoted byR2. The coefficient of

determination (R2

) is defined as the proportion of the total variation or dispersion in the

dependent variable (about its mean) that is explained by the variation in the independent or

explanatory variables (s) in the regression. In my study the R2

will measure how much of the

variations in the Inflation in Pakistan at long run is explained by the variation in Money Supply

and Import Price respectively, in Pakistan at long run.

R2 =

Explained Variation in Inflation (INFt )Total Variation in Inflation (INF t )

R2 =

Σ ( INF−INF )2

Σ ( INF−INF )2

In the simple regression analysis the square root of the coefficient of determination ( R2) is the

absolute value of the coefficient of correlation, which is denoted by r. That is,

R = √ R2

This is simply a measure of degree of association or co variation that exists between variables

Inflation and Money Supply, and Inflation and Import Price.

Adjusted R 2

Adjusted R2

is a modification of R2

that adjusts for the number of explanatory terms in a

model. UnlikeR2, the adjusted R

2 increases only if the new term improves the model more than

26

would be expected by chance. The adjusted R2

can be negative, and will always be less than or

equal toR2.

It is denoted by R2

R2 = 1 – (1 - R

2)

n−1n−k

Where n is the no. of observations or sample data points and k is the no. of the parameters or

coefficients estimated.

Co-integration test

Cointegration is an econometric property of time series variables. If two or more series are

themselves non-stationary, but a linear combination of them is stationary, then the series are said

to be cointegrated. It is often said that cointegration is a means for correctly testing hypotheses

concerning the relationship between two variables having unit roots.

The two main methods for testing for cointegration are:

1. The Engle-Granger two-step method.

2. The Johansen procedure.

In the study, the Johnson procedure is used to test the cointegration between variables.

Co-integration test for Inflation and Money Supply can be expressed as follows:

INFit = βo +β i MSit + ε t

Where, i = 1, 2, 3, 4, 5, 6………

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Hypothesis

Ho: There is no co integration is present between Inflation and Money Supply (MS t) at the

significance level in Pakistan, β = 0

H1: There is co integration is present between Inflation and Money Supply (MS t) at the

significance level in Pakistan, β ≠ 0

Now the trace statistics will be used for testing the above hypothesis.

Then if the result is that there is no cointegration present between Inflation and Money Supply,

the Granger Causality test will be used to show the short run relationship between Inflation and

Money Supply, while if the result are, there is cointegration present between Inflation and

Money Supply at significance level then the ECM will be used between Inflation and Money

Supply, so that the result about both short run and long run relationship can be obtained.

Error correction model (ECM)

The ECM will be run with the data at level from as well as at 1st difference form also.

Long run relationship

Hypothesis

Ho= There is no relationship present between Inflation and Money Supply in Pakistan in long run

at the significant level, β = 0

H1= There is relationship present between Inflation and Money Supply in Pakistan in long run at

the significant level, β ≠ 0

28

Now the t-test and F-test will be used for testing the above hypothesis.

Short run relationship

Hypothesis

Ho= There is no relationship present between Inflation and Money Supply in Pakistan in short

run at the significant level, β = 0

H1= There is relationship present between Inflation and Money Supply in Pakistan in short run at


T-Statistics

After an estimation of a coefficient, the t-statistics for that coefficient is the ratio of the

coefficient to its standard error. That can be tested against a t distribution to determine how

probable it is that the true value of the coefficient is really zero.

The test statistic is a t-score (t) defined by the following equation

t= [(INFt - MSt) – d] / SE, where x1 is the mean of sample1, x2 is the mean of sample 2.

Analysis of Variance

The overall explanatory power of the entire regression can be tested with the analysis of

variance. This uses the value of the F statistics, or F ratio. Specifically, the F statistic is used to

test the hypothesis that the variation in the independent variables explains a significant

proportion of the variation in the dependent variable. Thus, we will use the F statistic to test the

null hypothesis that all the regression coefficients are equal to zero against the alternative

hypothesis that they are not all equal to zero.

29

The value of the F statistic is given by

F =

Explained variation / ( k - 1)Total variation / ( n k )

Where, n is the number of observation and k is the number of regression coefficient. It is because

the F statistics is the ratio of two variances that this test is often referred to as the analysis of

variance. I will calculate the F statistics in terms of the coefficient of determination as follows:

F =

R2 / (k -1 )(1- R2 ) / ( n - k )

Here R2

represent the coefficient of determination between Inflation and Money Supply in

Pakistan in long run.

Then we will compare the calculated value of the F statistics a critical value from the table of the

F distribution. If the calculated value of the F statistics exceeds the critical value of the F

distribution. I will reject the null hypothesis that there is no significant relationship between

Inflation and Money Supply in Pakistan in long run, and I will accept the alternative hypothesis

at 5 % level of significance that not all the coefficient equal to zero, and vice versa.

Co-integration test for Inflation and Import Price can be expressed as follows:

INFit = βo +β i MP + ε t

Where, i = 1, 2, 3, 4, 5, 6………

Hypothesis

30

Ho: There is no co integration is present between Inflation and Import Price at the significance

level in Pakistan, β = 0

H1: There is co integration is present between Inflation and Import Price at the significance level

in Pakistan, β ≠ 0


Then if the result is that there is no cointegration present between Inflation and Import Price, the

Granger Causality test will be used to show the short run relationship between Inflation and

Import Price, while if the result are, there is cointegration present between Inflation and Import

Price at significance level then the ECM will be used between Inflation and Import Price, so that

the result about both short run and long run relationship can be obtained.

Error correction model (ECM)

The ECM will be run with the data at level from as well as at 1st difference form also.

Long run relationship

Hypothesis

Ho= There is no relationship present between Inflation and Import Price in Pakistan in long run at

the significant level, β = 0

H1= There is relationship present between Inflation and Import Price in Pakistan in long run at



31

Short run relationship

Hypothesis

Ho= There is no relationship present between Inflation and Import Price in Pakistan in short run

at the significant level, β = 0

H1= There is relationship present between Inflation and Import Price in Pakistan in short run at


T-Statistics

After an estimation of a coefficient, the t-statistics for that coefficient is the ratio of the

coefficient to its standard error. That can be tested against a t distribution to determine how

probable it is that the true value of the coefficient is really zero.

The test statistic is a t-score (t) defined by the following equation

t= [(INFt - Mpt) – d] / SE, where x1 is the mean of sample1, x2 is the mean of sample 2.

F- Test and Analysis of Variance

We will use the F statistic to test the null hypothesis that all the regression coefficients are equal

to zero against the alternative hypothesis that they are not all equal to zero.

The value of the F statistic is given by

F =

Explained variation / ( k - 1)Total variation / ( n k )

32

Where, n is the number of observation and k is the number of regression coefficient. It is because

the F statistics is the ratio of two variances that this test is often referred to as the analysis of

variance. I will calculate the F statistics in terms of the coefficient of determination as follows:

F =

R2 / (k -1 )(1- R2 ) / ( n - k )

Here R2

represent the coefficient of determination between Inflation and Import Price in

Pakistan in long run.




Inflation and Import Price in Pakistan in long run, and I will accept the alternative hypothesis at

5 % level of significance that not all the coefficient equal to zero, and vice versa.

Multi cointegration Analysis

The Multi cointegration Model

The multi cointegration model will be used for testing the cointegration between Inflation,

Money supply and Import Price.

INFt = βo + β1MSt + β2IPt + ε t

I is dependent variable while MS and IP are the independent variables. Whileε t is the error

affect the Inflation in Pakistan while we will just check that how much changes in Money Supply

and Import Price.

33

Then we will calculate the values of βo, β1, β2, and then we will calculate the value of R2

and

adjusted R2

and at last we will use F statistics to test the hypothesis that the variation in the

Money Supply and Import Price explains a significant proportion of the variation in the Inflation.

Cointegration Test

Hypothesis

Ho: There is no co integration is present between Inflation, Money Supply and Import Price at the


H1: There is co integration is present between Inflation, , Money Supply and Import Price at the



Error Correction Model (ECM)

The ECM model will be used for the finding the effects of changes in Money Supply and Import

Price on Inflation in Pakistan and to test the whether Money Supply and Import Price explains

significant variation of Inflation or nor? Is yes, then how much?

Hypothesis

34

Ho: The Money Supply and Import Price combine do not explain a significance proportion of the

variation in Inflation in Pakistan in long run, β = 0.

H1: The Money Supply and Import Price combine explain a significance proportion of the

variation in Inflation in Pakistan in long run, β ≠ 0.

We will test above hypothesis by using F statistics.

F =

R2 / (k -1 )(1- R2) / ( n - k )

Here R2

represent the coefficient of determination between Inflation, Money Supply, and

Import Price in Pakistan in long run.




Inflation, Money Supply and Import Price in Pakistan in long run, and I will accept the

alternative hypothesis at 5 % level of significance that not all the coefficient equal to zero, and

vice versa.

35

CHAPTER NO 5

Data Analysis

36

Chapter 5

Data Analysis

Unit root test:

Use the test “Augmented Dickey Fuller” and see that the data is stationary or non-stationary on

the level, 1st difference and 2nd difference. All the data are stationary on the 2nd difference.

Inflation

Augmented- Dickey Fuller Unit Root Test on D (INF, 2)

Null Hypothesis: D(INF,2) has a unit root

Exogenous: Constant

Lag Length: 4 (Automatic based on SIC, MAXLAG=7)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -5.088395 0.0005

Test critical values: 1% level -3.752946

5% level -2.998064

10% level -2.638752

*MacKinnon (1996) one-sided p-values.

37

First of all, to check the stationary property of the Inflation study we apply Augmented Dickey

Fuller test at level, 1st difference and 2nd difference therefore the series of Inflation is stationary

on 2nd difference at 1% significance level because the Augmented Dickey-Fuller Test statistic

value (5.088395) is greater than the critical value at 1% level (3.752946). As the P value is less

than 0.05 so we reject the null hypothesis in favor of alternative hypothesis which show this

series is stationary and there is no unit root.

Money Supply

Augmented- Dickey Fuller Unit Root Test on D (MS, 2)

Null Hypothesis: D(MS,2) has a unit root

Exogenous: Constant


t-Statistic Prob.*



5% level -2.976263

10% level -2.627420


First of all, to check the stationary property of the Money Supply on study we apply Augmented

Dickey Fuller test at level, 1st difference and 2nd difference therefore the series of Money Supply 38

is stationary on 2nd difference at 1% significance level because the Augmented Dickey-Fuller

Test statistic value (4.478232) is greater than the critical value at 1% level (3.699871). As the P

value is less than 0.05 so we reject the null hypothesis in favor of alternative hypothesis which

show this series is stationary and there is no unit root.

Import Price

Augmented- Dickey Fuller Unit Root Test on D (MP, 2)

Null Hypothesis: D(MP,2) has a unit root

Exogenous: Constant


t-Statistic Prob.*



5% level -2.998064

10% level -2.638752


First of all, to check the stationary property of the Import Price on study we apply Augmented

Dickey Fuller test at level, 1st difference and 2nd difference therefore the series of Import Price is

stationary on 2nd difference at 1% significance level because the Augmented Dickey-Fuller Test

statistic value (6.664508) is greater than the critical value at 1% level (3.752946). As the P value 39

is less than 0.05 so we reject the null hypothesis in favor of alternative hypothesis which show

this series is stationary and there is no unit root.

Johansen Co-integration Test:

Co-integration:

Co integration is an econometric property of time series variables. If two or more series are

themselves non stationary, but a linear combination of them is stationary, then the series are said

to be co integrated. It is often said that co integration is a mean for correctly testing hypothesis

concerning the relationship between two variables having unit roots. If the results show that there

is no co-integration between the variables then Granger Causality Test will be used to show the

short run relationship between the variables. But, if there is no co-integration between the

variables the there will be used Error Correction Model to show the long run relationship

between the variables.

40

Co integration test for Money Supply, Import Price and Inflation:

Date: 12/18/09 Time: 23:41

Sample (adjusted): 1978 2005

Included observations: 28 after adjustments

Trend assumption: Linear deterministic trend

Series: MS INF MP

Lags interval (in first differences): 1 to 1

Unrestricted Cointegration Rank Test (Trace)

Hypothesized No. of CE(s) Eigen value

TraceStatistic

0.05Critical Value Prob.**

None * 0.731322 56.50835 29.79707 0.0000At most 1 * 0.412374 19.70958 15.49471 0.0109At most 2 * 0.158231 4.822984 3.841466 0.0281

Trace test indicates 3 cointegrating eqn(s) at the 0.05 level

* denotes rejection of the hypothesis at the 0.05 level

**MacKinnon-Haug-Michelis (1999) p-values

41

INFt = βo + β1MSt + β2IPt + ε t

Where, i=1, 2, 3, 4, 5…..

Ho: There is no co integration is present between Inflation, Money Supply and Import Price at the


Versus

H1: There is co integration is present between Inflation, , Money Supply and Import Price at the



Co-integration test represents the long run relationship among the variables. The results show

that there is a long run relationship between the Inflation Money Supply and Import Price. The

results also show that the trace value is greater than the critical value which shows that there is a

long run relationship in these variables. The co-integration test indicates that there are three co-

integration equations and reject the null hypothesis and accept alternative hypothesis at the 0.05

level of significance as shown. Trace value indicates 3 equations at the 0.05 level.

42

Error Correction Model: (ECM)

Dependent Variable: D(INF)

Method: Least Squares

Date: 12/18/09 Time: 23:43

Sample (adjusted): 1978 2005

Included observations: 28 after adjustments

Variable Coefficient Std. Error t-Statistic Prob. C 0.885727 3.324317 2.643926 0.0267

LgD(MP) 0.606741 0.307312 1.974349 0.0419LgD(MS) 2.67E-11 2.30E-11 2.170306 0.0322LgMP(-2) -0.086942 0.244181 2.740128 0.0174LgMS(-2) -2.92E-12 1.45E-11 2.422857 0.0235LgINF(-2) -0.088661 0.302572 -2.07929 0.0337

R-Squared 0.817432Adjusted R-squared 0.796514Durbain-Watson 2.190545F-statistic 24.46032Prob(F-statistic) 0.001407

The ECM will be run with the data at level form as well at 2nd difference form.

Hypothesis

43

Ho= There is no relationship present between Inflation, Money Supply and Import Price in

Pakistan in long run at the significant level, β = 0

Versus

H1= There is relationship present between Inflation, Money Supply and Import Price in Pakistan

in long run at the significant level, β ≠ 0


When the cointegration test identify that there is a long run relationship among the variables,

we will test the ECM rather than the Granger Causality test. ECM is basically used to

investigate the long run and short run relationship between the variables. By applying it we

find the following results.

In these results, C = 0.885727 shows constant coefficient β1 and β2 are the partial coefficients

respectively. The value of β1 is 0.606741 shows that one unit change in Import Price brings

0.606741 units change in dependent variable Inflation and there is a positive relationship

between the Inflation and Import Price in long run and reflects the null hypothesis at 0.0419

probability. While the value of β2 is 2.67E-11 shows that one unit change in Money Supply

brings 2.67E-11 units change in dependent variable Inflation and there is a positive

relationship between the Inflation and Money Supply in long run and reflects the null

hypothesis at 0.0322 probability.

R-squared or overall goodness:

44

It measures the proportion of variability in the values of the dependent variable explained by

its linear relation with the independent variables. In my study it will measure how much of

the variation in Inflation in Pakistan at long run is explained by the variation Import Price

and Money Supply. It is computed by

R2 =

Explained Variation in Inflation (INFt )Total Variation in Inflation (INF t )

The value of it in my study is 0.817432 represents that the variation in dependent variable

Inflation are 81% explained by the independent variables Import Price and Money Supply in

Pakistan.

Adjusted R-squared:

Adjusted R2

is a modification of R2

that adjusts for the number of explanatory terms in a

model. UnlikeR2, the adjusted R

2 increases only if the new term improves the model more

than would be expected by chance. The adjusted R2

can be negative, and will always be less

than or equal toR2.

It is denoted by R2

R2 = 1 – (1 - R

2)

n−1n−k

45

The value of it in my study is 0.796514 represents that the variation in dependent variable

Inflation is 79% explained by the independent variables Import Price and Money Supply in

Pakistan.

F-Statistics:

It is computed by

F = R2/(k−1)

(1−R2)(n−k )

If its value is greater than its probability then we reject the H0 and accept the H1. In my study

F-statistics value 24.46032 is greater than its probability 0.001407. So, it indicates that

independent variables Import Price and Money Supply jointly affect the dependent variable

Inflation. At the end, the value of Durbin Watson test is 2.19 shows positive auto correlation.

After these result, we say that our model is good fit.

46

CHAPTER NO 6

CONCLUSION

47

Chapter 6

Summary

The present study has been made to understand the relationship between import price, money

supply and inflation in Pakistan by applying different techniques and produced different results .

To check the stationary of the dependent and independent variables applied the unit root test.

This test shows that the data is stationary at 2nd difference on (ADF).

To check the relationship between the variables, cointegration test is applied altogether on all the

variables. The prob. Value which is less than 0.05 shows that import price, money supply and

inflation are co integrated with each other, which indicates that the result is good.

At the end to check the long run relationship between the variables, error correction model is

applied. The results of ECM shows that all variables have long run relationship with each

other. Because the value of t-statistic is more than 2, the prob. value of ECM is also less than

0.05, the value of R-squared is greater than adjusted R-squared, the value of Durban-Watson

48

stat is also more than 2 and the prob. of f-statistic is 0.001407 which shows that the model is

good and relationship between all variable is very strong.

CONCLUSION

In this paper an effort has been made to understand the relationship between import price, money

supply and inflation in Pakistan. This study has investigated the determinants of inflation for the

period 1976-2005 in the case of Pakistan. This paper employs the co integration analysis and

error correction model to investigate the effect of import price and money supply on inflation.

The Inflation has been used as dependent variable while Import Price and Money Supply as

independent variables were used to investigate the impact of inflation created by such

independent variables in the economy of Pakistan. The overall conclusion is that we find

significant relationship between dependent variable (inflation) and independent variables

( Import Price and Money Supply). The overall conclusion is that import price and money supply

has a long-run positive impact on inflation in Pakistan.

In this study there are some limitations. One limitation of this study is the use of only import

price and money supply data. While others variables also affect the inflation, like interest rate,

49

technical change and human capital growth etc and others macro economic variables under

devolutionary policies. In this situation, the direction of the inflation is undetermined. Future

research should try to use mutual available to investigate it in Pakistan. Researchers interested in

extending this study should try to investigate the response of other variables in the model. This

will help understand the effect of import price and money supply on inflation on the economy as

a whole.

CHAPTER NO 7

References

50

References:

Fisher, S. Sahay, and R, Vegh, C, 2002, “Modern hyper – and high inflations Journal of

Economics Literature 40(3), 837- 80.

Khan, Mohsin (2005). ‘Inflation and Growth in MCD Countries,’ Mimeo, International

Monetary Fund.

Vogel, R.C. (1974), The Dynamics of Inflation in Latin America: 1950-1969, American

Economic Review, vol. 64, No. 1, pp102-113

Qayyum, Abdul (2006), “Money, Inflation, and Growth in Pakistan”, Pakistan Institute of

Development Economics. 45: 2 (Summer 2006) pp. 203–212.

Khan, M. S., and A. Schimmelpfennig (2006) Inflation in Pakistan: Money or Wheat?

International Monetary Fund. (Working Paper 06/60.

51

Khan, A. H. and M. A. Qasim (1996). “Inflation in Pakistan Revisited.” Pakistan Development

Review, 35: 747-759.

Husain and khan (2005) Money Income, and Prices in Pakistan: An Investigation of Causal

Relations with Shifts. Presented at Nurturing Minds Seminar Pakistan Institute of Development

Economics, Islamabad.

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

Review, 45: 203–212

Qadir and Abdul Aleem (2007). Global Research Project: Pakistan Country

Report. Dhaka: Global Research Project Workshop.

Wasim Shahid (2006) “Sources of Growth in Pakistan’s Large Scale Manufacturing

Sector: 1955-56 to 1980-81.” Pakistan Economic and Social Review, 27: 139-159

Sarel, M. D. J. Robinson and Anjum (1996) . Growth and Productivity in ASEAN Countries.

IMF Working Paper No. 97/97. Washington, D.C.: IMF.

Choudhry, U. E. and M. Khan and Kennedy et.al (2003) “The Exchange Rate and Consumer

Price in Pakistan: Is Rupee Devaluation Inflationary?” Pakistan Development Review, 41: 107

120.

Safdar.A & Omer.F (2009). “Inflation and Growth: An Estimate of the Threshold

Level of Inflation in Pakistan.” SB- Research Bulletin, 1: 35-44.

52

Sergent, T. J. and Harris (2004).“Some Unpleasant Monetarist Arithmetic.” FRBM Quarterly

Review, 5, 3.

Balke, Nathan, and Saqib et.al (2009) Understanding the Price Puzzle. Economic and Financial

Policy Review (Fourth Quarter). Federal Reserve Bank of Dallas.

Khan, Mohsin S., and Hanif (2006) Threshold Effects in the Relationship between Inflation

and Growth. IMF Staff Papers 48:1, 1–21.

Robert.J (1960-1990) Monetary and Structural Sources of Inflation in Pakistan.

Unpublished M. Phil. dissertation. Islamabad: Department of Economics, Quaid-i-

Azam University.

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Final Thesis on the Determinants of Inflation in Pakistan

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