An Evaluation of Consumption Function for Pakistan Based on Time Series Analysis
Besides gross domestic product, aggregate consumption is the single most important macroeconomic variable which affects various sectors of the economy, directly or indirectly. For example, consumption is said to be the biggest component of aggregate demand and hence is a major determinant of economic fluctuations in an economy. Besides these well known effects of consumption, it also has a number of other effects which are very relevant from the policy perspective. For instance, variations in consumption are strongly associated with variations in government tax revenues (in particular where bulk of tax revenue is collected through consumption taxes), variations in the balance of trade, inflation and so on. Keeping this immense importance of aggregate consumption in mind, it is important to know the sources that cause variations in aggregate consumption. This very topic is under serious scrutiny since the times of Keynes (1936) but no single answer has been reached as yet. In particular, there are still debates on the differences of short run and long run consumption functions and on the relevance of current income as a source of variation in consumption. This study has been designed to seek answers for some of the debated issues in the area. The study utilizes time series data from 1971 to 2012 and most of the variables mentioned relevant in the literature. As is the routine in contemporary time series based econometric analysis, we have checked all the variables for their order of integration. Since most of the variables under consideration were found to be non stationary, the use of conventional ordinary least square was ruled out and we searched for our answers using the relatively new cointegration analysis. The relevant technique, in our case, was the Johansen and Juselius (1992) conintegration (JJ hereafter) technique which has a number of advantages over the Engle- Granger cointegration technique. Supervisor:- Dr. Abdul Qayyum Co-Supervisor:- Dr. Hafsa Hina
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