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Future Prospects of Small Scale Industrial Sector Of Punjab: An Empirical Assessment

Keywords: Forecasts , ARIMA , Akaike information criterion , Scheward Bayesian criterion , correlogram.

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Abstract:

Present study seeks the generation of forecasts of number of units, employment, capital formation and production of small scale industrial sector of Punjab for ensuing decade till 2019-20.Forecasts have been generated for the lead time of thirteen years by using Auto Regressive Integrated Moving Average (ARIMA) model, based on identifying the pattern followed by past values of a each variable and then extrapolating the pattern in the past for short period. The analysis of forecasted figures has revealed that the fixed capital investment and production would experience significant growth during the lead time of thirteen years from 2007-08 to 2019-20. Number of units and employment are expected to observe meager growth during this period indicating low possibility of absorption of labour force in this sector. In the light of the forecasts for low employment, it is imperative that the state government to take concerted economic policy initiatives to strengthen the industrial base in Punjab. In this regard catastrophic changes are required so far as industrial policy of Punjab is concerned.

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