Journal Press India^®

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The main aim of this paper is to examine both short run and long run effects of various factors on agricultural productivity in India. The present study used the annual time series data covering the time period from 1980 to 2013. Johansen cointegration and vector error correction model are adopted in order to examine the objective of the study. The study has analysed the relative effectiveness of various factors like Irrigation (PGIA), Fertilizer (FERT), Electricity (ELCT), Private investment in agriculture (PII) and Non-product specific support to inputs (NPSS) on agricultural productivity. The cointegration results suggest that there is a long run equilibrium relationship between all the determinants and agricultural productivity. The vector error correction model indicates that there is long run causality running from PGIA, FERT, NPSS, ELCT, and PII to Productivity meaning that all the factors have significant influence on productivity in long run. However, as regards short run, only PGIA and PII have significant impact on agricultural productivity. The study suggests that the government should take initiative for non-product specific support to major inputs like organic fertilizer, power and irrigation and also promote private investment in agricultural sector to enhance agricultural productivity which will go a long way in development of agricultural sector.

Keywords

Agricultural productivity; Johansen cointegration; Vector error correction.

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