Forecasting Exports Of Industrial Goods From Punjab - An Application Of Univariate Arima Model
AbstractThe present study is an attempt to build a Univariate time series model to forecast the exports of industrial goods from Punjab for ensuing decade till 2020. The study employs Box-Jenkin’s methodology of building ARIMA (Autoregressive Integrated Moving Average) model to achieve various objectives of study. Annual time series data for exports of industrial products have been culled from Directorate of Industries, Punjab for the period 1974-75 to 2007-08. Different selected models were tested by various diagnostic tests to ensure the accuracy of obtained results. The results revealed that during the days to come, exports of industrial products from Punjab are going to experience a sharp decline in growth as compared to past three decades in which growth maintained two digit level. In light of the forecasts, concerted efforts on the part of Government, entrepreneurs, industrialists, farmers and producers are the need of the hour to establish a healthy state economy and its export sector.
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Bibliographic InfoArticle provided by University of Petrosani, Romania in its journal Annals of the University of Petrosani - Economics.
Volume (Year): 10 (2010)
Issue (Month): 4 ()
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Web page: http://www.upet.ro/
ARIMA; Forecasting; Box-Jenkin Method; Akaike Information Criteria; Schwarz Bayesian Information Criteria;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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