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Regression Methodology

To analyze the impact of oil prices on inflation in Pakistan, I used the annually data from 1980 to 2010. The price of oil and inflation are often seen as being connected in a cause and effect relationship. As oil prices move up or down, inflation follows in the same direction. The reason why this happens that oil is a major input in the economy, it is used in critical activities such as fueling transportation and heating homes and if input cost increases , so should the cost of end products. Inflation and Exchange rate also shows positive relationship, as it plays a very vital role in determining the monetary policy. So, it’s very necessary to control the inflation to safeguard the economy. According to the Quantity Theory of Money, when money supply increases, the price level increases which results in inflation. The quantity theory of money states that there is a direct relationship between the quantity of money in an economy and the level of prices of goods and services sold. According to QTM, if the amount of money in an economy doubles, price levels also double, causing inflation (the percentage rate at which the level of prices is rising in an economy). The consumer therefore pays twice as much for the same amount of the good or service.

Monetarists say that a rapid increase in money supply leads to a rapid increase in inflation. Money growth that surpasses the growth of economic output results in inflation as there is too much money behind too little production of goods and services. In order to curb inflation, money growth must fall below growth in economic output.

During the procedure of planning and decision making in any empirical analysis related to economics, regression technique helps a lot as it tackles the problem of uncertain circumstances and helps to understand the nature of relationship between underlying variables and in model building.

In this paper for regression analysis OLS Regression analysis is used because of its mathematical simplicity and its results are also very simple and easy to understand.

Model Specification

In this part the specification of the appropriate method for the analysis is necessary in order to prove that wheather the oil prices is going to affect the inflation rate in the economy, for this we need to develop a particular model for it. Following from the discussion and theoretical literature, the equation can be summarized as follows,

inf = β0 + β1 inft-1 + β2 opt + β3 reer+ β4ms+ β5un+ εt

Where,

inf = Difference of Inflation determined by CPI

ms = Difference of Money Supply M2

op = difference of yearl oil prices

er = Difference of exchange rate

un= Difference of unemployment

εt= Error term

Where εt is the white noise disturbance term following the assumptions of classical linear regression model.

Usually the data is non-stationary. For the purpose of testing for the stationary of data and determination of the order of integration of each variable, the Augmented Dickey Fuller (ADF) test of Unit Roots [Dickey and Fuller (1979, 1981)] is performed on the univariate time series. Phillips and Perron (PP) test for unit root is also performed which is similar to ADF test .

EMPIRICAL RESULTS

Test for Statio